text:
Date of Completion

Embargo Period

Hanchen Huang; Nejat Olgac

Field of Study

Mechanical Engineering

Master of Science

Open Access

Open Access

Panic during emergency building evacuation can cause crowd stampede, resulting in serious injuries and casualties. Agent-based methods have been successfully employed to investigate the collective human behavior during emergency evacuation in cases where the configurational space is extremely simple - usually one rectangular room - but not in evacuations of multi-room or multi-floor buildings. This implies that the effect of the complexity of building architecture on the collective behavior of the agents during evacuation has not been fully investigated. Here, we employ a system of self-moving particles whose motion is governed by the social-force model to investigate the effect of complex building architecture on the uncoordinated crowd motion during urgent evacuation. In particular, we study how the room door size, the size of the main exit, the desired speed and the friction coefficient affect the evacuation time and under what circumstances the evacuation efficiency improves.

Major Advisor

George Lykotrafitis


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After School Care

After School Care is for children ages 5-12

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text:
George Mason University

Decision Analysis in Healthcare

Introduction to Decision Analysis

Welcome to the world of decision analysis. This section will introduce you to the purpose and organization of this book.   This book describes how analytical tools can be used to help healthcare managers and policymakers make complex decisions. It provides numerous examples in health care settings including benchmarking performance of clinicians, project implementation, scenario planning, resource allocation, analyzing impact of HMO penetration, setting insurance rates, root cause analysis and negotiating employment agreements.

Nearly 20 years ago, Alemi (1986) wrote an article arguing for training health care administrators in decision analysis. Despite widespread acceptance of the idea at the time, as demonstrated by published commentaries, decision analysis has not caught on with health care administrators as much as it has in other industries.  Overall, application of decision analysis in other industries is growing (Keefer, Kirkwood, Corner 2004). MBA students are more likely to receive instruction in decision analysis and when they go to work, they are more likely to use these tools. Goodwin and Wright (1998) give several descriptive examples of use of decision analysis by managers: DuPont uses it to improve strategic decision making, nuclear planners used decision analysis to select counter measures to Chernobyl disaster. ICI America uses it to select projects, Phillips Petroleum uses it to make oil exploration decisions, US military uses it to acquire new weapon systems, EXEL Logistics uses it to select a wide area network, ATM Ltd uses it for scenario planning. The list goes on. In contrast, there are few applications to health care management reported in the literature. This is not so ironic if it were not for the fact that there are numerous applications of decision analysis to clinical decision making and an increasing emphasis in health care to base clinical decisions on evidence and data (Detsky et al. 1998). Decision analysis is used widely by clinicians to understand best course of treatment. This book hopes to change the situation in one of two ways. First, the book will highlight the application of decision analysis to health care management. Health care managers can see for themselves how useful analysis can be in central problems they face.  Second, this book covers decision analysis in enough depth so that readers can apply the tools to their own settings.

This book  is ideally suited for students in health care administration programs.  It may help these programs to develop a courses in decision analysis.  At the same time, the book will be useful for existing survey courses on quantitative analysis in terms of providing a more in-depth understanding of decision analysis so that students feel confident in their abilities to apply these skills in their careers.

The book is also intended for clinicians interested in application of decision analysis to improving quality of care.  Often, practicing physicians, Medical Directors, Nurse Mangers and Clinical Nurse Leaders need to take a system perspective of patient care.  This book provides them with analytical tools that can help them understand systems of care and evaluate the impact of these operations on patient outcomes.    There are a number of books on clinical decision analysis.  This book includes applications to quality improvement that are not typically discussed in other clinical decision analysis books, including root cause analysis, assessing severity of patients' illness and benchmarking performance of clinicians.   These are novel tools that can serve clinicians well if they want to improve health care settings.

Finally, this book may be useful in training of health care policy analysts.  Policy analysts have to provide accurate analysis under time pressure.  Decision analysis is one tool that can help them provide relevant analysis in a timely fashion.  The book contains a number of application of decision analysis to policy decisions including the design of health insurance programs and security analysis.

Organization of the Book

This book is organized in two broad sections. In the first section various analytical tools (multi-attribute utility models, Bayesian probability models, and decision trees) are introduced. In particular, the following chapters are organized:

  1. Modeling Preferences
    A demonstration of how to model a decision-maker's values and preferences. This chapter shows how to construct multi-attribute value and utility models, tools that are helpful in evaluation tasks. In particular, it shows how to use multi-attribute value model in constructing severity indices.
  2. Measuring Uncertainty
    An introduction to concepts of probability and causal networks. This chapter lays the ground work for measuring uncertainty by subjective assessment of probability. It shows how to assess the concept of probabilistic independence, a concept central to model building.
  3. Modeling Uncertainty
    A demonstration of how to assess the probability of uncertain, rare events based on several clues. This chapter introduces Bayes odds form and shows how it can be used in forecasting future events. In particular, the chapter applies the Bayes Odds form to assessment of market for a new type of Health Maintenance Organization.
  4. Decision Trees
    A demonstration of how to combine utility and uncertainty in analyzing options available to healthcare managers. Includes analyzing sensitivity of conclusions to errors in model parameters. It shows how a decision tree can be used to analyze the impact of a Preferred Provider Organization on an employer.
  5. Group Decision Making
    Advice on how to obtain the preferences and uncertainties of a group of decision makers. This chapter describes the Integrative Group process.

In the second section, the tools in Part I are applied to various management decisions, including:

  1. Root-Cause Analysis
    Application of Bayesian networks to root-cause modeling. Use of causal networks to conduct root-cause analysis of sentinel events.
  2. Cost-Effectiveness Analysis
    Use of decision trees for analyzing cost effectiveness of clinical practices and cost of programs.
  3. Risk Analysis
    Application of Bayesian probability models to assessment of privacy and security risks.
  4. Program Evaluation
    Use of decision-analysis tools for program evaluation. Use of Bayesian probability models to analyze markets for new health services.
  5. Conflict Analysis
    Use of multi-attribute value modeling in analyzing conflict and conflict resolution. This chapter shows how multi-attribute value models could be used to model conflict around family planning program. In addition, an example is given of negotiation between an HMO manager and a physician.
  6. Rapid Analysis
    This chapter shows how subjective and objective data can be combined in order to conduct a rapid analysis of business and policy decisions.
  7. Clinical benchmarking
    Use of decision analysis to construct measures of severity of illness of patients and to compare clinicians' performance across different patient populations.

It is imperative that health care managers become facile with formal decision analysis techniques so that they will be competent to analyze and devise effective solutions to the complex situations they will encounter in their careers. This book provides the basis for the acquisition of skills which will help them do so. Good decisions based on a systematic consideration of all relevant factors and stakeholder opinions and values lead to good outcomes, both for those involved in the decision making process, and for the customers who are directly impacted by the consequences and effects of such decisions.

Introduction to Decision Analysis

This chapter introduces the idea behinds decision analysis, the process of analysis and its limitations.  The discussion is directed toward decision analysts who help individuals in healthcare institutions responsible for making tough choices. Anytime a selection must be made among alternatives, a decision is being made, and it is the role of the analyst to assist in this process.  When decisions are complicated and require careful consideration and systematic review of the available options, the analyst role becomes paramount. As you will learn in this chapter, the analyst’s job is to separate complex decisions into component parts and then reconstitute the final decision from those parts. Some decisions are harder than others to make, and this chapter provides a discussion of why that might be. For instance, some problems are poorly articulated. In other cases, the causes and effects of potential actions are uncertain. There may be confusion about what environmental factors could impact the decision. Given these uncertainties, you will learn how to clarify and simplify such problems without diminishing the usefulness or accuracy of the analysis. As an analyst, it will be your job to provide structure to the problem, to reduce uncertainty about potential future events that may impact the situation, to help decision makers clarify their values and preferences, and to help reduce conflict among decision makers who may have different opinions about the utility of various options. This chapter goes on to outline specifically the steps involved in decision analysis including problem exploration and goal clarification, identification of decision makers, problem structuring, quantifying values and uncertainties, analyzing the courses of action and finally recommending the best course of action. This chapter will provide you with a solid foundation in your understanding of the purpose and process of decision analysis. Later chapters will introduce more specific tools and skills which are meant to build upon this foundation.

Who is an Analyst?

This book is addressed to analysts who are trying to assist health care managers in making complex and difficult decisions.  The Webster Merriam's dictionary definition of system analysis can be used to define who is an analyst.   An analyst studies the choices between alternative courses of actions, typically by mathematical means, in order to reduce uncertainty and align it with decision makers' goals. �

This book is laid out as if the decision maker and the analyst are two different people.  Of course, a decision maker might want to self analyze their own decision.  In these circumstances, the tools described in the book can be used but the decision maker must play both the role of the analyst and the decision maker.  When mangers want to think through their problems, they can use the tools in this book to analyze their own decisions without the need for an analyst.

Who is a Decision Maker?

One of the first tasks of an analyst is to clarify who makes the final decision and on what timetable.  Many chapters in this book  assume that a single decision maker is involved in the process.  Sometimes more than one decision maker may be involved.  Chapter 11, on Conflict Analysis, and chapter 6, on Group Decision Making, are intended for situations when multiple decision makers are involved.,

Through out the book, the assumption is that at least one decision maker is always available to the analyst.  This is an over simplification of the reality of organizations.  Sometimes it is not clear who the decision maker is.   Other times, an analysis starts with one decision maker who leaves his/her position midway through the analysis; one person commissions the analysis and another person receives the findings.   Sometimes, an analyst is asked to conduct an analysis from a societal perspective, where it is difficult to identify clear decision makers.   All of these variations make the analysis process more difficult.   �

What is a Decision?

This book is about using analytical models to finding solutions to complex decisions.  Before proceeding, various terms should be defined.  Lets start with a definition of a decision.  Most individuals go through their daily work without making any decisions.  They react to events without taking the time to decide about them.  When the phone rings and if they are available, they pick it up and answer.  In these situations, they are not deciding but just working.  Sometimes, however, they need to make decisions.  If they have to hire someone and there are many applicants, they need to make a decision.

One is making a decision as opposed to following routines, when one has several plausible courses of actions.  According to the Webster Dictionary, deciding is to arrive at a solution that ends uncertainty or dispute about what to do.  A decision is made when a course of action is selected among alternatives.   More formally, a decision has following components:

  • A set of alternatives or options

  • Each alternative leads to a series of consequences over which the decision maker has little control

  • The decision maker is uncertain about what might happen.

  • The decision maker has different preferences about outcomes associated with various consequences.

A decision involves choosing among uncertain outcomes with different values.

What is Decision Analysis?

The Webster Dictionary defines analysis as separation of a whole into its component parts.  Decision analysis is the process of separating a complex decision into its component parts and using a mathematical formula to reconstitute the whole decision from its parts.  It is a method of helping decision makers make simple and familiar choices and using a mathematical model to infer from these choices what would the decision maker had preferred to do in the complex intractable decision.

An Example

The means by which the analysts can capture uncertainties and values is exemplified by a hypothetical situation faced by the head of the state agency responsible for evaluating nursing home quality: A nursing home has been overmedicating its residents in an effort to restrain them, and the administrator of state agency must take action to improve care at the home. The possible actions include fining the home, prohibiting admissions, and teaching the home personnel more appropriate use of psychotropic drugs.

Any real‑world decision has many different effects. For instance, the state could institute a training program to help the home improve its use of psychotropic, but the state's action could have effects beyond changing this home's drug utilization practices. The nursing home could become more careful about other aspects of its care such as how it plans care for its patients. The nursing home industry could become convinced that the state is enforcing stricter regulations on administration of psychotropic drugs. All these effects are important dimensions that should be considered during the analysis and in any assessment performed afterward.

The problem becomes more complex because the agency administrators must consider which constituencies' values should be taken into account and what their values are regarding the proposed actions. For example, the administrator may want the state to portray a tougher image to the nursing home industry, but one constituent, the chairman of an important legislative committee, may object to this image. So the choice of action will depend on which constituencies' values are considered and how much importance each constituency is assigned.

Why are Some Decisions Hard to Make?

Decisions are hard to make because of uncertainty about outcomes of the decisions and confusion about value of various outcomes.   Three types of uncertainty typically confront the decision maker:

  • Poorly articulated problem.  The decision maker is unsure or unaware of the nature of the problem. This causes difficulties because a successful solution must start with correct identification of the problem. For example, if the nursing home was simply ignorant of how to use psychotropic drugs appropriately, a decision to prohibit further admissions would just alienate the nursing home without solving the problem. In this case, training would not only solve the problem but also foster a positive relationship between the home and the state. If, however, the nursing home knew exactly what it was doing‑cutting costs with chemical restraints‑‑a consultation and training program could be fruitless. But while it is important to know as much as possible about the nursing home's reasons for its drug policy, one can never be certain about those reasons, and almost any decision includes an element of diagnostic uncertainty.

  • Poorly understood cause and effects.  The decision maker is not sure what action will lead to the desired outcome.  In general, too little is known about most problems‑‑even those that seem clearly understood‑‑to be sure that a specific action will lead to a particular outcome. This is true even if no major events intervene. In the nursing home example, even if the inappropriate chemical restraint was clearly based on ignorance and the state had already won the court case, one cannot be sure training would correct the problem. Perhaps the home personnel did not have the education or motivation to use the drugs properly.

  • Poorly understood environment.  The decision maker is not sure about what external events may change the alternatives available.  In characterizing a decision problem, the analyst must identify which future events will affect the relationship between action and outcome, and analyze what the impact of those events will be.  In short, the analyst must have a crystal ball of sort to see the future.  Suppose that during the time the decision maker is deciding to prohibit further admissions, the constitutionality of state regulation of admissions is being challenged in court.  If the state loses the court test, then selecting that option (prohibiting admissions) could be futile.  Future events can be divided into two important groups: (1) unlikely events that would have monumental consequences and (2) likely events that would have lesser but significant consequences.

Decisions are also hard to make because the values of different outcomes may not be clear or different constituencies may disagree on value of various outcomes.   The more the confusion about what the decision makers really want, the more difficult to analyze it.:

Prototypes for Decision Analysis

         Real decisions are complex.  The purpose of analysis is not to capture decisions in all its complexity.  The goal is not to impress, and in the process overwhelm, the decision maker about the analyst's ability to capture all possibilities.  The goal of analysis is to simplify the decision enough to meet the decision maker's needs.  An important challenge then is to determine how to simplify an analysis without diminishing its usefulness and accuracy.

         A useful simplification is to ignore some uncertainties, so the value of an action is assumed to be more "certain" than it really is‑in other words, the chance of an event is either near zero or one. For instance, in deciding which departments need additional funds, the decision maker might choose to assess current levels of needs and ignore the uncertainty about future needs. Of course, such simplifications are only appropriate when using them will make little difference in the results of the analysis.

          Alternatively, the analyst may assume that uncertainty is the only issue and that the other values and actions can be addressed without the help of analysis. For example, the principal challenge in strategic planning may be diagnosing what would our target customers need. Presumably, after knowing unmet customers needs, the decision maker's action would be relatively clear and the analyst would not need to examine the decision maker's preferences over different outcomes.

          Over the years, as analysts have applied various tools to decisions some prototypes have emerged.  If an analyst can recognize that a decision is like one of the prototypes in his/her arsenal of solutions, then he/she can quickly address the problem.  Each prototype leads to some simplification of the problem and specific analytical solution.  The existence of these prototypes helps in addressing the problem with known tools and methods.   These prototypes include:

  1. Identify the problem

  2. Reduce uncertainty about future events

  3. Clarify values

  4. Reduce conflict among various constituencies

  5. Do it all

Prototype 1. Identify the problem

Analysts can help decision makers by providing a structure to the problem.  Sometimes decision makers do not truly understand the problem they are addressing.  This lack of understanding can be manifested in disagreements about the proper course of action. Each member of a decision making team may prefer a reasonable action based on his or her limited perspective of the issue. An analyst can promote better understanding of the decision by helping policy makers to explicitly identify:

  • Individual assumptions about the problem and its causes
  • Objectives being pursued by each decision maker
  • Constituencies having different perceptions and values
  • Options available
  • Factors that influence the desirability of various outcomes
  • Principal uncertainties that complicate the problem

Figure 1: Decision Maker Faces a Difficult Decision As Options, Values &
Uncertainties in the Decision are not Clear

The analyst can listen to the decision maker and let him or her articulate various aspects of a problem.  As Figure 1 shows, the analyst usually seeks to understand the nature of the problem by clarifying the values and uncertainties involved in the problem.  When the problem is fully described, the analyst can provide an organized summary to the decision makers, helping them see the whole and its parts.

Prototype 2. Reduce Uncertainty

An analyst can help decision makers by reducing their uncertainty about future events.  Decision makers are sometimes not sure what will happen if an action is taken.  They may not be sure about the state of their environment. What is the chance that a fine will really change the way the nursing home uses psychotropic drugs? What is the chance that if a hospital administrator opens a stroke unit their competitors will not do the same?

             Through the process of analyzing uncertainty, the decision's options and their relative desirability can be clarified. What causes system malfunctions? What are the chances a similar event will recur? How likely is action A to lead to outcome B? Often the answers to such questions are vague at best. Returning to our example, although you probably have some clues about whether the nursing home's overmedication was caused by ignorance or greed, usually the clues are neither equally important nor measured on a common scale. The analyst helps to compress the evaluations to a single scale for comparison.  The analyst uses various tools to forecast the future.

Figure 2: Decision Maker Faces a Difficult Decision Because
Outcomes of their Action is Uncertain

The forecast is based on a set of clues.  Some clues suggest the target event might occur, other clues suggest the opposite.  The analyst distills the implications of often contradictory clues into a single forecast.  Deciding on the nature and relative importance of these clues is difficult because people tend to assess complex uncertainties poorly unless they can divide them into manageable components. Decision analysis can help make this division by using probability models that combine components after their individual contributions have been determined. This book addresses such a probability model‑Bayes' theorem‑‑in chapter 4.

Prototype 3.  Clarifying Values

An analyst can help decision makers clarify their values and preferences.  In some situations the options are clearly identified and uncertainty plays a minor role.  In these decisions the primary concern is to examine the options in terms of a complex set of values that have differing levels of importance and are measured on different scales. The Decision Maker's actions will have many outcomes some of which are positive and others negative (see Figure 4).  One option may be preferable on one dimension but unacceptable on another.  Somehow the decision maker must trade off the gains in one dimension with losses in another.

Figure 3:  Decision Maker Faces a Difficult Choice
Because their Actions May Lead to Positive & Negative Outcomes

In traditional attempts to debate an option, advocates of one option focus on the dimensions that show it having a favorable outcome, while opponents attack it on dimensions on which it performs poorly. Optimally, a decision analysis provides a mechanism to force consideration of all dimensions‑a task that requires answers to these questions:

  • Which objectives are paramount?

  • How can an option's performance on a wide range of measuring scales be collapsed into an overall measure of relative value?

For example, a common value problem is how to allocate limited resources to various individuals or options. The British National Health Service, with a fixed budget, deals with this issue quite directly. Some money is allocated to hip replacement, some to community health services, and some to long‑term institutional care for the elderly. Many people who request a service after the money has run out must wait until the next year.  A chief financial officer has to tradeoff various projects in different departments and decide on allocation of a budget for the unit.  The decision analysis approach to these questions uses a process called multi-attribute value (MAV) modeling, which is introduced in chapter 2.

Prototype 4.  Reduce Conflict

An analyst can  help decision makers understand conflict better by modeling the uncertainties and values that different constituencies see in the same decision.  Common sense tells us that people with different values tend to choose different options. The principal challenge facing a decision making team may be understanding how different constituencies view and value a problem and determining what trade‑offs will lead to a win-win, instead of a win‑lose,  solution.  Decision analysis addresses situations like this by developing a MAV model for each constituency and using these models to generate new options that benefit all.

Figure 4:  Decision Makers Face a Difficult Decision
Because they Differ in the Outcomes they Prefer

Consider for example a contract between an HMO and a clinician.  The contract will have many components.  There are at least two different perspectives on almost every issue.  The parties would need to balance cost, benefits, professional independence, required practice patterns, and many other issues.  An analyst can identify the issue and highlight the preferences of the parties.  Then conflict can be understood and steps can be taken to avoid escalation of conflict to a level that disrupts the negotiations.

Prototype 5.  Do it all

Of course, a decision can have all of the elements of the last four prototypes.  In these circumstances, the analyst must:

  • Identify who are the various decisions makers and their differences.

  • Identify possible actions, of which usually there are many.

  • Identify possible outcomes of an action, cost is one outcome but other outcomes are also relevant

  • Identify major uncertainties (events that, if they were to occur, would interfere with an action's leading to a certain outcome)

  • Attach values to those outcomes

  • Analyze the data available to recommend a course of action

Figure 5:  Components of a Decision

In this prototype, the analyst needs to address both uncertainty about future outcomes as well as confusion about value of these outcomes.  An example is making a decision about merger between two hospitals.  There are many decision makers.  The decision structure itself is not clear.  There are many uncertain consequences associated with the merger.  The impact of merger on various outcomes (cost, access, quality, etc.) are not clear nor is it clear how much each outcome should be emphasized and why.

Steps in Decision Analysis

         Good analysis is about the process not the numbers.  One way to analyze a decision is for the analyst to conduct an independent analysis and present the results to the decision maker in a brief paper. This is usually not very helpful and emphasizes the findings as opposed to the process.  Decision makers are more likely to accept an analysis in which they have actively participated.

          The preferred method is to conduct decision analysis is as a series of increasingly more sophisticated interactions with the decision maker.   At each interaction, the analyst listens and summarizes what the decision maker speaks about.  In each step, the problem is structured and an analytical model is created.  Through these cycles, the decision maker comes to self insight and the analysis documents his/her conclusions.

           Of course, sometimes decisions are made in groups.  Here again the goal is to conduct a decision conference that engages the decision makers in various steps of the analysis.  A decision conference starts with a day‑long retreat during which the decision making team agrees upon the conceptual structure of the problem. In the next day, the group agrees on objectives, possible actions, uncertainties, outcomes, values, probabilities, and perhaps other topics.  Sometimes values and uncertainties are quantified.  The conference prods decision makers to think carefully about the issues and the tradeoffs they are willing to make.  It structures the problem.  The team emerges from this short retreat with better understanding of their decision.

            Whether the analysis is done for one person or several people, there are several distinct steps in decision analysis.  A number of investigators have suggested steps in conducting decision analysis (Soto, 2002; Philips, et al. 2004; Weinstein et al. 2003).  Soto, working in the context of clinical decision analysis, recommends that all analysis should take the following steps:

  1. "State clearly the aim and the hypothesis of the model

  2. Provide the rationale of the modeling

  3. Describe the design and structure of the model

  4. Expound the analytical time horizon chosen

  5. Specify the perspective chosen and the target decision makers

  6. Describe the alternatives under evaluation

  7. State entirely the data sources used in the model

  8. Report outcomes and the probability that they occur

  9. Describe medical care utilization of each alternative

  10. Present the analyses performed and report the results

  11. Carry out sensitivity analysis

  12. Discuss the results and raise the conclusions of the study

  13. Declare a disclosure of relationships

Based on commonly suggested steps, we suggest the following:

Step 1. Explore the Problem & the Role of the Model

Problem exploration is the process of understanding why the decision maker wants to solve a problem.  The analyst needs to understand what would the resolution of the problem achieve. This understanding is crucial because it helps identify creative options for action and sets some criteria for evaluating the decision.  The analyst also need to clarify what is the purpose of the modeling effort ( to keep track of ideas, to have a mathematical formula that can replace the decision maker in repetitive decisions, to clarify issues to the decision maker, to help others understand why the decision maker chose a course of action, to document the decision, to help the decision maker arrive at self insight, to clarify values, to reduce uncertainty, etc.).

Let's return to the head of the Division of Nursing Home Administration who was trying to decide what to do about the nursing home that was restraining its residents with excessive medication. The problem exploration might begin by understanding the problem statement: "Excessive use of drugs to restrain residents." Although this type of statement is often taken at face value, several questions could be asked. How should nursing home residents behave? What does restraint mean? Why must residents be restrained? Why are drugs used at all? When are drugs appropriate, and when not? What other alternatives does a nursing home have to deal with problem behavior?

The questions at this stage are directed at (1) helping to understand the objective of an organization, (2) defining frequently misunderstood terms, (3) clarifying the practices causing the problem, (4) understanding the reasons for the practice, and (5) separating desirable from undesirable aspects of the practice.

During this step, the decision analyst must determine which ends, or objectives, will be achieved by solving the problem. In the example, the policymaker must determine whether the goal is primarily to

  • Protect an individual patient without changing overall methods in the nursing home

  • Correct a problem facing several patients‑in other words, change the home's general practices

  • Correct a problem that appears to be industry wide

Once these questions have been answered, the decision analyst and policymaker will have a much better grasp on the problem. The selected objective will significantly affect both the type of actions considered and the particular action selected.

Step 2. Identify Decision Makers, their Perspective and Timeframe

Who makes the decision is not always clear.  Some decisions are made in groups, others by individuals.  For some decisions there is a definite deadline for others there is no clear timeframe.  Some decisions have already been made before the analyst came on board; others involve much uncertainty and the analyst needs to sort them out.  Sometimes the person who sponsors the analysis is preparing a report for a decision making body, not available to the analyst.  Other times the analyst is in direct contact with the decision maker.  Decision makers may also differ in the perspective they want the analysis to take.  Sometimes providers costs and utilities are central, other times patients' values derive the analysis.  Sometimes societal perspective is adopted other times the problem is analyzed from the perspective of a company.  Decision analysis can help in all of these various situations but in each of them the analyst should explicitly specify the decision makers, the perspective of the analysis and the time frame for deciding.  The analyst should sort out who are the real decision makers, what is their perspective and when should the decision be made.

The specification of decision maker does not stop with identifying the individual's involved.  It is important to understand the constituencies, whose ideas and values must be present in the model.  A decision analysis can always assume that only one constituency exists and that disagreements arise primarily from misunderstandings of the problem, not from different value systems among the various constituencies. But when several constituencies with different assumptions and values, the analyst must examine the problem from the perspective of each constituency.

A choice must also be made about who will provide input into the decision analysis. Who will specify the options, outcomes, and uncertainties? Who will estimate values and probabilities? Will outside experts be called in? Which constituencies will be involved? Will members of the policymaking team provide judgments independently, or will they work as a team to identify and explore differences of opinion?  Obviously, all of these choices depend on the decision maker and an analyst should simply ask question and not supply answers to the questions.

Step 3. Structure the Problem

Problem structuring adds conceptual detail to the general structure provided by step 2. The goals of structuring the problem are to clearly articulatey

  • What the problem is about, why it exists, and whom it affects

  • The assumptions and objectives of each affected constituency

  • A creative set of options for the decision maker

  • Outcomes to be sought or avoided

  • The uncertainties that affect the choice of action

Structuring is the stage in which the specific set of decision options is identified. Although generating options is critical, it is often overlooked by decision makers‑a pitfall that can easily promote conflict in cases where diametrically opposed options falsely appear to be the only possible alternatives. Often, creative solutions can be identified that better meet the needs of all constituencies.  To generate better options, one must understand the purpose of analysis.  The process of identifying new options relies heavily on reaching outside the organization for theoretical and practical experts, but the process should also encourage insiders to see the problem in new ways.

It is important to explicitly identify the objectives and assumptions of the decision makers. Objectives are important because they lead to the preference of one option over the other. If the decision making team can understand what each constituency is trying to achieve, the team can analyze and understand its preferences more easily. The same argument holds for assumptions. Two people with similar objectives but different assumptions about how the world operates can examine the same evidence and reach widely divergent conclusions.

Take, for example, the issue of whether two hospitals should merge.   Assume that both constituencies‑those favoring and those opposing such merger‑‑want the hospital to grow and prosper.  One side believes that the merger will help grow faster and the other side believes that the merger would make the organization lose focus.  One side believes that the community will be served better by competition and another side believes the community will benefit from collaboration between the institutions.  In each case, the assumptions (arid their relative importance) influence the choice of objectives and action, and that is why they should be identified and examined during problem structuring.

Problem structuring is a cyclical process‑the structure may change once the decision makers have put more time into the analysis.  The cyclical nature of the structuring process is desirable, not something to be avoided. � An analyst should be willing to go back and start all over with new structure and new set of options.

Step 4. Quantifying Values

The analyst should help the decision maker break complex outcomes into their components and weight the relative value of each component. The components can be measured on the same scale, called a value scale, and an equation can be constructed to permit the calculation of the weighted average of the scores.

Value has two sides: cost and benefits. Cost is typically measured in dollars and may appear straightforward.  But true costs are complex measures and difficult to measure.  This is the case because certain costs, such as loss of goodwill, are non-monetary and difficult to track from operation budgets. Furthermore, even monetary costs may be difficult to allocate to specific operations as overhead and other shared cost may have to be allocated in methods that seem arbitrary and not precise.

Benefits need to be measured based on various constituencies' preferences.  Assuming that benefits and the value associated with the benefits are un-quantifiable can be a major pitfall because it can place them subservient to costs in a formal analysis of policy, even though values often drive the actual decision.  By assuming values cannot be quantified, the analysis may ignore concerns most likely to influence the decision maker.

Step 5. Quantifying Uncertainties

The analysts interacts with decision makers and experts to quantify uncertainty about future events. For example, if the nursing home inspectors were asked to estimate the chance that the home's chemical restraint practice resulted from ignorance or knowing intention to save money, they might agree that the chances were 90 percent ignorance and 10 percent intent. In some cases, additional data are needed to assess the probabilities. In other cases, there is too much data available. In both cases, the probability assessment must be divided into manageable components. Bayes' theorem (see chapter 4) provides one means for disaggregating complex uncertainties into their components.

Step 6. Analyze & Recommend Course of Action

Once values and uncertainties are quantified, the analyst uses the model of the decision to score the relative desirability of each possible action. This can be done in different ways depending on what type of a model has been developed.  One way is to examine the expected value of the outcomes.  Expected value is the weighted average of the values associated with outcomes of each action.  Values are weighted by the probability of occurrence of each outcome. Suppose, in the nursing home example, two actions are possible:�

A1 = Consult
A2 = Stop admission

The possible outcomes are:

  1. Industry changes:  Chemical restraint is corrected and industry "gets the message that the state intends tougher regulation"

  2. Only one home changes:  The home receiving the citation changes but the rest of industry does not "get the message"

  3. No change:  The home ignores the citation and there is no impact on the industry

Suppose the relative desirability of each outcome is:

  • Industry changes has best value, 100

  • Only one home changes, 25

  • No change, 0

The probability that each action will lead to each outcome is shown in the six cells of the matrix in Figure 3.

  Industry changes Only one home changes No change
Action 1:  Consult with the home 0.05 0.60 0.35
Action 2:  Stop admissions to the home4S 0.40 0.20 0.40
Probability of an Action Leading to an Outcome
Outcomes: Industry changes Only one home changes No change
Values for each outcome: 100 25 0

Figure 3:  A Decision Matrix For Nursing Home Regulatory Actions

The expected value principle says the desirability of each action is the sum of the values of each outcomes of the action weighted by probability of the outcome.  If  pij is the probability of action "i" leading to outcome "j" and Vj is the value associated with outcome "j", then expected value is calculated as:

Expected value of action "i"  =∑pij Vj

In the case of our example, expected values are:

Expected value of consultation =  0.05 * 100+ 0.60*25 + 0.35*0 = 20F

Expected value for stopping admission = 0.40 *100 + 0.20 *25 + 0.40 * 0 = 45

This analysis suggests that the most desirable action would be to stop admissions because its expected value is larger than consultation.

Step 7: Conduct Sensitivity Analysis

The analyst interacts with the decision maker to identify how various assumptions in the analysis affect the conclusion.  The previous analysis suggests that "Consultation" is inferior to "Stopping Admission". But this should not be taken at face value because the utility and probability estimates might not be accurate. Perhaps the source of those estimates was guesses, or the estimates were average scores from a group, some of whose members had little faith in the estimates. In these cases, it would be valuable to know whether the choice would be affected by using a different set of estimates. Stated another way, it might make sense to determine how much an estimate would. have to change to alter the choice of "preferred" action.

Usually, one estimate is changed until the expected value of the two choices become the same.  Of course, several estimates can also be modified at once, especially using computers. Sensitivity analysis can be vital not only to examining the impact of errors in estimation but also to determining which variables need the most attention (e.g., reduction in disagreement and/or increase in confidence).

At each stage in the decision analysis process, it is possible and often essential to return to an earlier stage to

  • Add a new action or outcome
  • Add new uncertainties
  • Refine probability estimates
  • Refine utility estimates

This cyclical approach offers a better understanding of the decision problem and fosters greater confidence in the analysis. Often the decision recommended by the analysis is not the one implemented, but the value of the analysis remains because it increases understanding of the issues. Phillips refers to this as the theory of requisite decisions‑once all parties agree that the problem representation is adequate for reaching the decision, the model is "requisite":

From this point of view, decision analysis is more an aid to problem solving than a mathematical technique, Considered in this light, decision analysis provides the decision maker with a process for thinking about their actions.  It is a practical means for maintaining control of complex decision problems that involve risk, uncertainty, and multiple objectives. (Phillips 1984, p. 26)

Step 8:  Document and Report Findings

Even thought the decision maker has been intimately involved in the analysis and is probability not surprised at its conclusions, it is important to document and report the findings.  An analysis has its own life cycle.  It may live well beyond the current decision makers.  It is important to document all considerations that were put into the analysis.  Individuals who did not participate in the decision may wonder how it was arrived at.  A clear documentation, one that uses multi-media to convey the issues, would help create a consensus behind a decision.

Limitations of Decision Analysis

It is difficult to evaluate the effectiveness of decision analysis because often no information is available on what might have happened if decision makers had not followed the course of action recommended by the analysis.   One way to improve the accuracy of analysis is to make sure that the process of analysis is followed faithfully.  Rouse and Owen (1998) suggest asking the following questions about decision analysis to discern if it was done accurately:

  1. "Were all realistic strategies included?
  2. Was the appropriate type of model employed?
  3. Were all important outcomes considered?
  4. Was an explicit and sensible process used to identify, select and combine the evidence into probabilities
  5. Were utilities assigned to outcomes plausible and were they obtained in a methodologically acceptable manner
  6. Was the potential impact of any uncertainty in the probability and utility estimates thoroughly and systematically evaluated"

These authors also point out four serious limitations to decision analysis which are important to keep in mind:

  1. "Decision analysis may oversimplify problems to the point that they do not reflect the real concerns of the patient nor accurately represent the perspective from which the analysis is being conducted.
  2. Available data simply may be inadequate to support the analysis.
  3. Utility assessment, in particular, assessment of quality of life may be problematic.  "Measuring quality of life, while conceptually appealing and logical, has proven methodologically problematic and philosophically controversial.
  4. Outcomes of decision analyses are not amenable to traditional statistical analysis. Strictly, by the tenets of decision analysis, the preferred strategy or treatment is the one that yields the greatest utility (or maximizes the occurrence of favorable outcomes) no matter how narrow the margin of improvement."

In the end, the value of decision analysis (with all of its limitations) is in the eye of the beholder.  If the decision maker can understand and have new insights into a problem, if the problem and suggested course of action can be documented and communicated to others more easily, a decision maker may judge decision analysis, even imperfect analysis, as useful.

What do you know?

In the following, describe a non-clinical work related decision.  Describe who makes the decision, what actions are possible, what outcomes results and how are these outcomes evaluated.
  1. Who makes the decision?
  2. What actions are possible (list at least two actions)?
  3. What are the possible outcomes?
  4. Besides costs what other values enter these decisions and whose values are considered relevant to the decision?
  5. Why are the outcomes uncertain?
Please email your responses to your instructor.

To assist you in reviewing the material in this lecture, please see the following resources:

  1. Listen to Introduction.  See the slides.

Narrated lectures require use of  Flash.

More & References

  • References

    Detsky AS, Naglie G, Krahn MD, Naimark D, Redelmeier DA . Primer on medical decision analysis: Part 1. Getting started Med Decis Making, 1998  Apr-Jun;18(2):237-8.

    Goodwin P, Wright G.  Decision Analysis for Management Judgment  UK: Wiley, 1998

    Gustafson DH, Holloway DC.  1975. "A Decision Theory Approach to Measuring Severity of Illness." Health Services Research 10: 97‑196.

    Gustafson DH, Fryback DG, Rose JH, Prokop CT, Detmer DE, Rossmeissl JC, Taylor CM, Alemi F, Carnazzo AJ.. 1983. "An Evaluation of Multiple Trauma Severity Indices Created by Different Index Development Strategies." Medical Care 21: 674‑91.

    Gustafson DH, Fryback DG, Rose JH, Yick V, Prokop CT, Detmer DE, Moore J. 1986. "A Decision Theoretic Model for Severity Index Development." Medical Decision Making 6 (1): 27‑35.

    Health Services Research Group. 1975. "Development of the Index of Medical Under service." Health Services Research (Summer).

    Johnson, S., and D. Gustafson. 1989. Final Report of the Psychiatric Emergency Severity Index Project, Maine Health Information Center, Augusta.

    Keefer DL, Kirkwood CW, Corner JL. Perspective on decision analysis applications, 1990-2001 Decision Analysis Vol. 1, No. 1, March 2004, pp. 4–22.

    Rouse DJ, Owen J. Decision analysis. Clin Obstet Gynecol. 1998 Jun;41(2):282-95.

    Soto J. Health economic evaluations using decision analytic modeling. Principles and practices--utilization of a checklist to their development and appraisal. Int J Technol Assess Health Care. 2002 Winter;18(1):94-111.

    Philips Z, Ginnelly L, Sculpher M, Claxton K, Golder S, Riemsma R, Woolacoot N, Glanville J. Review of guidelines for good practice in decision-analytic modelling in health technology assessment. Health Technol Assess. 2004 Sep;8(36):iii-iv, ix-xi, 1-158.

    Phillips, L. D. 1984. "A Theory of Requisite Decision Models." Acta Psychologica 56: 29‑48.

    Weinstein MC, O'Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, Luce BR; ISPOR Task Force on Good Research Practices--Modeling Studies. Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--Modeling Studies. Value Health. 2003 Jan-Feb;6(1):9-17.

Recommended Reading (logoff after each article, requires library membership)

Societies and Associations

Other Sites

This page is part of the course on Decision Analysis, the lecture on Introduction to Decision Analysis.  This page was last edited on 10/19/17 by Farrokh Alemi, Ph.D.   ©Copyright protected.  TThis page is based on a chapter with the same name published by Gustafson DH, Cats-Baril WL, Alemi F. in the book  Systems to Support Health Policy Analysis:  Theory, Model and Uses/a>, Health Administration Press: Ann Arbor, Michigan, 1992.


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Should local radio pay royalties?

Nab_logo_2 If you thought the battle over webcasting royalties was hard fought, just wait until the National Assn. of Broadcasters and the RIAA drop the gloves over the issue of performance royalties for over-the-air stations. Having gotten some of the preliminary sparring out of the way, the two behemoths face off Tuesday in D.C. in front of the House Judiciary Subcommittee on Courts, the Internet and Intellectual Property. Like the chairman of the full committee, Subcommittee Chairman Howard Berman (D-North Hollywood) is very protective of the entertainment industry. On the other hand, there aren't many lobbying groups in D.C. that can match the clout of the NAB, largely because of the role that TV and radio stations continue to play in lawmakers' re-election campaigns.

The title of the hearing suggests where Berman is leaning: it's dubbed "Ensuring Artists Fair Compensation: Update the Performance Right and Platform Parity for the 21st Century." I think it makes a lot of sense to have a common standard for royalty payments among broadcasters regardless of how their signal is delivered. Already, broadcasters of all stripes, whether they be terrestrial, satellite or Internet, pay similar percentage-of-revenue royalties to those who hold copyrights to the public performance of the songs. But the amounts paid to those who hold the recording copyrights are all over the map. At the high end, webcasters have to pay a fraction of a penny for each song streamed to each listener (although some small and non-commercial webcasters get a discount). At the low end, local radio stations pay nothing. XM, Sirius and cable-TV based services fall in between, paying a percentage of their revenues.

Fred von Lohmann of the Electronic Frontier Foundation has argued, in response to my previous post on this issue, that collecting more royalties wouldn't serve the basic purpose of copyright law. The point of copyrights is to provide an incentive for those who create music. With plenty of music being created, Fred says, there's no reason to obligate terrestrial broadcasters to provide more incentive by paying royalties. If anything, he said, the obligation should be dropped from webcasters so that they'll have parity with local stations.

That's a more persuasive argument than claiming that radio decreases music sales, which the industry lobbying group in favor of the new royalties contends. Geez, I thought it was piracy that was killing music. Or maybe home taping. Still, I think it's fair for record companies to ask Congress for a recalibration of the decades-old deal that allowed local stations to play music without paying for the rights to the recordings. There's no question that radio isn't driving the volume of sales that it used to generate -- nothing is in the file-sharing era. And just from a spectator's point of view, I love the idea of the RIAA and the NAB squaring off. Bring on the steel cage!

The comments to this entry are closed.

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Saturday, May 06, 2017

Interest piqued

I'm far, far from being a Christopher Nolan fanboy, but I have to admit, the new trailer for his forthcoming Dunkirk has a very pleasing look of realism about it.  (In reality, there probably will be plenty of CGI in it, but if you can't tell, it doesn't matter.)

Of course, it may look great but still have no emotional connection to the audience, and he did write it himself (which is a warning sign, given he and his brother did the God awful dialogue in Interstellar.)   But the claim is that Dunkirk is actually light on dialogue.

We shall see....

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The 360, 430, 458 are all evolutions of the same idea - the small V8 Ferrari. They all have a similarly lightened, sportier cousin. So why is the 360's called the Challenge when the 430's is the Scuderia? Why is the 458's called the Speciale? Why can’t they be consistent? Why is the 355 actually called the F355? Why is the 360's coupe called the Modena while the 458 is called the Italia? They’re all built in Modena, Italia.

Why did the F12 Berlinetta break tradition from the 550, 575 and 599? Why are only the 599 and F12 given the Berlinetta name? They’re all Berlinettas - it means 2-seat coupe! Why is are the 550 and 575 given the Maranello name? Why is the 575 actually called the 575M?

The less said about LaFerrari the better.

What’s an SA Aperta? Why not Barchetta? They’re the same damn idea. And why was the Barchetta called Pininfarina? They were all by Pininfarina back then.

I forgive the FF, for breaking tradition of its; 456 and 612 forefathers. It’s a very different car. But why not 630FF or something? FF in itself is a dumb name.

I’m all for different things having different names. But Ferrari keep building the same thing and giving it different names. That, and slapping on random titles to make a car more Italian or to give it more heritage. It’s marketing bullshit. It’s deliberately confusing.


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watch the social network movie

This is the much awaited 2010 movie that the related story is in the famous the birth of website namely that the idea of this movie by watching the social network movie is to see the story in the beginning of and the founder Mark Zuckerberg. A Harvard undergrad one night in his dorm that came in his ideacomes in his mind that in a fury of blogging and programming wanted to create a website that people want to check on the internet checkout website and to search their friends people that want to build website that offers friends pictures profiles that taking about the entire social experience in college.

More stories about the social network movie in the internet?


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“No Strings Attached” featuring Brandon Castillo

Theme: “No Strings Attached”
Storyteller: Brandon Castillo

Brandon Castillo shares how as a young college graduate, he embarks on a two-year journey of self-discovery in Madrid.

Make sure to follow our RSS, Podcasts, Social Media (Facebook & Twitter) streams and now our YouTube Channel to stay up to date on the published stories. So if you missed out on any of the past shows, you finally get your chance to catch up on the action.

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“Push The Envelope”

“Push The Envelope” Podcast is now LIVE

New Podcast for “Push The Envelope” in Partnership with Dallas Media Outlet, CentralTrack.com, as One Continuous Podcast

The Oral Fixation (An Obsession with True Life Tales) podcast is back for Season 5! We will be releasing each Season 5 show once a month in collaboration with Central Track starting with #PushTheEnvelope. Check out our new updated format edited by former storyteller Emily Trube including music by the amazing Daniel Hart & Dark Rooms! Click below, fill your cup with something warm & enjoy!!

In this episode, you’ll hear the following: Read more

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Showing posts with label The Dark Frigate. Show all posts
Showing posts with label The Dark Frigate. Show all posts

Saturday, 17 February 2007

Sailing on The Dark Frigate

The 1924 Newbery medalist, The Dark Frigate, is about a young sailor named Philip Marsham, and his adventures and misadventures on land and sea. His father, a sea captain, has lost his life at sea, and nineteen-year-old Philip shortly thereafter loses what money he inherited when forced to flee his dead father’s promised wife’s pub after a mishap with somebody else’s gun. Penniless but undaunted he wanders the roads of England, thinks of becoming a farmer, falls in with a kindly Scottish smith, a madman, and then a couple of vagabond seamen. He glimpses his estranged grandparents, becomes engaged to a pretty bar maid, and duels with a gamekeeper before signing on to a ship called the Rose of Devon. And this is only in the first seventy pages. Crewing on the Rose of Devon means more adventures involving storms and pirates — which as one would expect leads in turn to more adventures yet.

Lloyd Alexander, in his 1971 introduction to The Dark Frigate, wrote that Charles Boardman Hawes “learned the sailor’s life from seafarers in Boston and Gloucester; from incredibly detailed research into ships’ logs, curious old volumes, and accounts of long-forgotten days” and also that Dawes considered the King James Bible “the greatest literary achievement of all time”. I haven’t a doubt of either statement. Both Dawe’s depth of research and biblical literary aesthetic are readily apparent from every page of this book.

The dialogue, the descriptions, the characters and the narrative all come across as authentically gritty and evocative with never a single nod to any popular conception of what seventeenth century seafaring life was like, such as a pirate-uttered “Yarrrr!” In writing The Dark Frigate, Charles Boardman Hawes managed to create that rarity in historical novels — one that is remarkably free of elements that date its actual time of writing. When I reviewed the 1923 Newbery winner, The Voyages of Dr. Dolittle which is set in the 1840s, I claimed that it was unmistakably a 1920s novel. The Dark Frigate, which is set in the 1650s, is a different animal altogether. If I did not know that it was originally published in 1923 I would have been at a loss to guess its publication date. I would definitely have known that it was a historical novel and not written in the seventeenth or even eighteenth centuries, but my estimated date of its writing might have fallen anywhere between 1850 and 1970. I can only hope I would at least have placed it in the twentieth century.

The Dark Frigate also does indeed echo the King James Version of the Bible in its literary tone. The KJV, originally published in 1611, would have made a fantastic resource for someone trying to recreate seventeenth-century diction and prose. But The Dark Frigate resembles the KJV Bible in another way that I am not convinced is so positive — in a certain spareness of its narrative. There is little if any exploration of characterization or internal conflict. The Dark Frigate is strictly a “by their works ye shall know them” affair. Characters are sketched out with flat, one-line descriptions such as “the woman had a bitter temper and a sharp tongue” or “Tom Jordon was an ugly customer when his temper was up and hot, but no man to nurse a grudge” and by what they say or do. Granted, there is so much action and the pace of events is so fast Dawes could barely have found room for things like internal monologues or extended conversations even if he had wanted to. And the characterizations are quite good so far as they go. Dawes paints no sentimental portraits of any of his cast, whether they be pirates and barmaids or gentlefolk and judges. There are no simple jolly souls or purely evil figures, his ruthless pirates do not have hearts of gold, and almost all share the rough humour and shrewdness a brutish environment engenders in all those who survive it.

However, as good as The Dark Frigate is as a story of adventure and as an evocative historical novel, I can’t help feeling that it lacks a certain depth that would have come from better characterization and more internal conflict. Though this may just be my contemporary sensibilities or personal tastes getting the better of me. Perhaps this only means Charles Boardman Hawes was better at entering into another time than I, but it could also mean that he failed to take me with him.


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This is Copland Symphony 3 violin excerpt from mvt 4 from Rehearsal 90 until 98.
(Sheet Music for this selection is currently unavailable. We apologize for the inconvenience)

Eduardo Mata: Dallas Symphony Orchestra, 2009

Aaron Copland: London Symphony Orchestra, 1991

Leonard Bernstein: New York Philharmonic, 1986

MIDI Practice Track:

This is the excerpt played an octave lower and super slow to make sure you are playing all the right notes.

Quarter Note = 45

Quarter Note = 65

Quarter Note = 80

Quarter Note = 100


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Call 405.515.8090 to make an appointment.

The elbow is a complex joint that consists of the upper arm bone (humerus) and one of the lower arm bones (ulna) connected by a hinge, or a joint that only moves in one direction. Although not protected by muscle or fat like most other joints, the elbow is one of the most important joints in the body, as it allows the arms to bend and twist.

Some of the most common elbow injuries include:

  • Biceps tendonitis
  • Dislocation
  • Bursitis
  • Biceps tendon rupture
  • Epicondylitis
  • Fractures

Many of these conditions can be treated through conservative methods, but some may require surgery to effectively relieve pain and restore function to the joint.

Possible Treatments and Procedures

Fracture Repair:

Because of its delicate nature, the elbow bone is vulnerable to fractures that can cause intense pain, swelling and an inability to move the arm. If a fracture is suspected, the doctor will perform a physical examination and X-ray imaging to confirm a fracture diagnosis. While many fractures can be treated through conservative methods such as immobilization and icing, surgery may be required for more severe cases.

Tommy John Surgery:

This is a surgical procedure performed to repair torn ligaments in the elbow after a damaging injury to the area. This procedure, named for Los Angeles Dodgers pitcher Tommy John, can effectively relieve pain and instability in patients with a torn or damaged ulnar collateral ligament (UCL). A torn UCL commonly affects pitchers, and could even end a baseball player’s career if severe enough.

During Tommy John surgery, the tendon in the forearm is used to recreate the damaged ligament and restore stability to the joint. Most patients achieve successful results from this procedure, although it often requires a lengthy recovery period of 12 to 18 months before athletes can return to activity.

Biceps Tendon Surgery:

The biceps tendon attaches muscles to the shoulder and also helps bend the elbow and rotate the forearm. Surgical treatment for a biceps tendon injury depends on the type and severity of the condition. The procedure may include simply shaving away the torn fibers, removing the torn tendon stump and reattaching the remaining tendon, or completely reattaching torn tendons with screws and sutures.

Elbow Arthroscopy:

Elbow arthroscopy is generally used for simple manipulations of the joint, such as fracture care, debridement and removal of bone fragments. It is also commonly used to confirm and examine abnormalities of the joint to provide a proper diagnosis and ensure that patients will recover in the shortest time possible.

Total Elbow Replacement:

Elbow replacement is performed to repair severe damaged within the elbow joint caused by osteoarthritis, fractures, tumors, tissue tears or other serious conditions. During the elbow replacement procedure, the damaged bone ends are removed from the joint and replaced with a prosthetic device that is held in place with bone cement and connected with a hinge. This procedure is performed under general anesthesia. Patients will need to undergo physical therapy after joint replacement in order to restore strength and stability to the joint before returning to physical activity.


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Thursday, March 21, 2013

Dear Sophia,

I wasn't sure where to write what I'm about to say. I knew you wouldn't begrudge the space here, so here it will go.

I need to vent, and maybe cry. There's a part of life I despise, which I have currently been stuck in on different levels for a while now: I like to call it limbo. Limbo and I don't get along, mostly because limbo never gets anywhere or achieves anything. Limbo may have a beginning, but no foreseeable end, and I can't stand that.

You could say I'm currently in childbearing limbo. It started October 29, 2012, when Daddy and I got married. We wanted children right away, and immediately proceeded to try. After about three months of frustration, I finally got the answer I wanted: "Pregnant." This, however, was followed by an awful, sinking feeling before each appointment with the obstetrician, and soon, a terminal diagnosis. While I will never say I am not grateful to have had you, I was in a constant state of worry. Should we just let you go? Would you come early? Would you die in the womb? Would we have time for Daddy to bless you before you passed away? Every day, I waited and waited, so unsure of everything except that I loved you.

Now, here we are again at square one, except square two is nowhere to be seen. As it is, I'm six days late, and have no solid idea if I'm pregnant or not. Each day, I wonder things like "Will my period come today?" or "Will I finally get a confirmation of pregnancy?" or even this gem: "Am I going to have a miscarriage since my levels aren't even high enough to confirm pregnancy at six days past my expected period?"

Pregnancy test manufacturers would like you to believe you should spend money on their test because it can tell you 4/5/6 days sooner than other brands. They claim it's 99% accurate, and you'll have great results if you test the day after your missed period. Well, that day has come and gone five-fold, and I still have yet to receive any definitive answer. What's even better is I called the office of the doctor I'll be seeing for this next pregnancy and they basically said not to even bother trying to see them, that they don't usually even see patients until they've missed a complete cycle. In other words, just wait until you're completely messed up in the head and then we'll see you, kthxbye. Great.

So, there it is. Wait, wait, and wait some more. Maybe my period will come. Maybe it won't. Maybe I'll turn green, shrink a few feet, and join a horde of ravenous, flesh-eating leprechauns. At least I'd be doing something! Ugh. I just feel so frustrated. At least if I'd gotten my period, I could move on to trying to get the next cycle. As it is, I don't even know when we'll be able to try again if I'm not pregnant. I just don't do very well with unknowns. I like definite goals and destinations, and this whole "wait and see" thing just doesn't sit well with me.

I have not been praying for patience, but apparently I'm in need of some anyway. *insert giant, frustrated sigh*

That is all.

(P.S. For those reading, prayers would be very much appreciated. If you couldn't tell, I'm going a little crazy with this whole waiting thing. Thank you.)

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The Exquisite Workings of Love {The Testimony of Bro. Billy Dela Fuente}

Meditating on Psalm 145.

I will extol You, my God, O King;
And I will bless Your name forever and ever.
2 Every day I will bless You,
And I will praise Your name forever and ever.
3 Great is the Lord, and greatly to be praised;
And His greatness is unsearchable. (vv. 1-3)

Now, we know that God is the source of love – pure, powerful, undying. God is love (1 John 4:8). He weaves bittersweet, yet, beautiful stories out of our lives. Psalm 145 is definitely a beautiful psalm that merits a story that will tug at our heartstrings. I read the psalm and I couldn’t help but put it side by side with the testimony I heard recently in our Church.

Psalm 145 extols the splendor of God’s majesty, His wondrous works and awesome acts, His greatness and goodness, compassion and mercy! How do we make this psalm become alive so that we can experience – hear, feel, taste – it to the full? I have a story for you.

I have written about Brother J before on this blog (I didn’t take the time to locate it – sorry!). The reason I can’t use his real name is because, his parents were advised not to divulge personal information about him while the case is on-going, except for the testimonies his father shares in church. To give you a brief background: Brother J surrendered his life to the Lord in his youth. Though he was the only one saved in the family, this didn’t deter him to serve the Lord fervently. He shared the Gospel to his father but he was only laughed at. His father was fiercely religious in the traditional way, bowing and praying before graven images.

Brother J wanted to help his family financially, so he applied for work abroad through an agency. He believed that the Lord would guide and protect him especially that he was young and innocent in the ways of the world. To make the story short, Brother J was hired to work in a factory in China. The day he would leave for China, he was instructed by the agency to fly to Singapore first, meet someone there, then proceed to China. As innocent and unsuspecting Brother J was, he met with the man in Singapore, received the parcel given him, then flew to China. At the airport there, he was at once handcuffed and whisked away to prison. He was accused of being a drug mule.

It’s been 5 years since that happened. His parents have long received the Lord Jesus Christ and been serving Him faithfully, often offering prayers and fasting. The father, Bro. Billy, has joined the Adults Choir. Every time he testifies, I cry. I cry for his son who’s languishing in jail in China. And I pray for him, too. Brother J’s original sentence was life. He didn’t waver in his faith in God. He praised, worshiped, and prayed. He requested for a Holy Bible and in the darkness of the prison, shared the Gospel to his fellow inmates. Even those who oversee the prisons took to him. The next time he was evaluated, his sentence was reduced to 26 years, then 18, then 14, and now 12. He’ll be evaluated again soon and the ardent prayer of the parents and the Church is for him to be freed already.

The Lord upholds all who fall,
And raises up all who are bowed down.
15 The eyes of all look expectantly to You,
And You give them their food in due season.
16 You open Your hand
And satisfy the desire of every living thing. (vv. 14-16)

Just recently, Brother J’s parents traveled to China to visit him. They were allowed by the Chinese Embassy at last. From Manila to China, Bro. Billy did nothing but pray and weep that they’d be able to touch and embrace their beloved son. They were told by the officials in the embassy that they could only see him through a thick glass and talk to him via telephone. But Bro. Billy was praying for a miracle. He wanted to embrace his son who was painfully missed.

Even when they were ushered into the receiving room, Bro. Billy didn’t stop praying and crying until his voice was hoarse and his eyes were red and puffy. While bowed down in his seat, someone put a hand on his stooped shoulders. When he looked up, he couldn’t believe his eyes! His beloved son was standing before him with his open arms. Hallelujah!

The Lord is righteous in all His ways,
Gracious in all His works.
18 The Lord is near to all who call upon Him,
To all who call upon Him in truth.
19 He will fulfill the desire of those who fear Him;
He also will hear their cry and save them. (vv. 17-19)

Brother J’s fervent love for Jesus Christ sees him through his hardest trial. It is actually Jesus’ love working powerfully in him. “We love Him because He first loved us” (1 John 4:19).

The Lord preserves all who love Him… (v. 20)

(Photo courtesy of my cousin Bill Raras).

If you have been blessed by your visit here, please like Our Healing Moments on Facebook and connect with me there. Thank you!

I might be linking up with these lovely blogs and Coffee for Your Heart.

Journey with Jesus,


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Wednesday, April 10, 2013

my human water fountain

I'm not sure what is so fascinating about this to him, but he does it constantly lately.  I'm not exaggerating when I say I cleaned up FOUR pools of water today.  Seriously!

On the up side, at least we don't have carpet.

It's a good thing he's real cute.  ;)

Now only if there was money being thrown at him like in a real fountain....

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Thursday, December 25, 2014

I'm walking backwards for Christmas

Saw this on a friend's Facebook and thought it was perfect for a Private Beach Christmas.  Wishing my loyal readers the compliments of the season and a democratic new year!

Monday, December 22, 2014

Basic Liar

Watching the news lately has become more of an ordeal than a pleasure; with various government ministers, mainland bigwigs and pro-government toadies talking total bollocks every day, there is always something to be irritated by.  But few of the many untruths emanating from our northern neighbours recently have left me so furious as Chen Zuoer's accusation that the British were cowards who surrendered meekly to the Japanese invaders who overran Hong Kong in 1941.

It may suit the Chinese Communist Party line to peddle this lie (designed, it seems, to reinforce their other lie that the Joint Declaration is China's business alone), but the historical reality is that the hopelessly outnumbered British and Commonwealth garrison fought bravely against the invaders for 16 days before, with no prospect of success, the then Hong Kong Governor reluctantly surrendered to avoid further loss of life.  A visit to the military cemeteries at Sai Wan and Stanley would show Chen the graves of many of those courageous men he falsely labels cowards.

As it happens, the father (now deceased) of a friend was one of those who fought the Japanese here before enduring more than three years of brutality as a prisoner, initially in a local PoW camp then as a slave labourer in a factory in Japan.  But apart from Hong Kong, Chen's statement is also a gross insult to all the British, Commonwealth and American servicemen who spent several years of their lives fighting against Japan.  My own father was one of them, a signaller on a Royal Navy ship which saw action in the Far East.  Without the efforts of those millions of men, it is quite probable that China today would still be under Japanese rule.

More on this story here and here.

Sunday, December 21, 2014

If at first you don't succeed, keep getting it wrong

The Pro-China Morning Post had three goes at getting the right headline for its lead story yesterday, and still failed each time.

Subtle - wrong!  Veiled - wrong!  Try "bleeding obvious".

Monday, December 08, 2014

Is you is or is you ain't?

Only a few weeks ago we were being told that the Umbrella Movement was being backed by insidious foreign forces bent on undermining China.  Now China's Ambassador to Britain tells us that external support for the protests is an "illusion".  I'm so confused...


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Friday, October 25, 2013

Geo 365: Oct. 25, Day 298: Otter Rock From Devils Punchbowl

After we left Hatfield Marine Science Center, we headed north to Devils Punchbowl, prior to driving up to Otter Rock- the high point in the left-middle of this panorama. (size options here- right click on the image) There's a lot going on in this photo. The most extraordinary aspect is the ring dike, displayed as a series of sea stacks outward and to the south (toward the viewer) of Otter Rock, where Columbia River Basalt reached the Pacific Ocean, flowed out onto the then-accumulating sediments of the Astoria Formation, and plunged into them, creating so-called invasive dikes. Not visible from this viewpoint, but clearly shown by the photo at the first link, there is actually a pair of ring dikes and some radial dikes as well. The sediments of the Astoria Formation have been tilted to the west at this location, and two generations of marine terraces have been developed on those rocks. What appears to be sandy beach deposits create an angular unconformity on the elevated terrace, where The Inn at Otter Crest has been built. In addition to the elevated terrace of Otter Crest, it looks as if there's a somewhat more poorly developed terrace at roughly the same elevation in the CRB headland beyond Otter Rock. A small waterfall drops to the beach this side of the stairway from the inn. Finally, I can't see enough detail to be absolutely certain, but there are number of linear grooves that are likely faults across the modern, sea-level terrace.

Like I said, a lot going on here.

Photo unmodified. May 6, 2013. FlashEarth location.

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Wednesday, September 06, 2006

to california. finally. head spun but happy. so much to do.

but first, fog in west texas, floods in el paso, tan lakes in the desert, red rocks, oasis, wind farms
phoenix is the place where we get lost. kevin finnerty? beacons?

churned air, the heat

descending and then-

here we are; bright and bright and bright and bright

K. Lorraine Graham said...

Are you in the north or the south?

Michelle Detorie said...

Hey! We're in the Santa Barbara area -- Goleta, right next to UCSB. Is that close to you? I have a sister in LA so I think I'll be in that area pretty often. I'd love to meet!

is this real?


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Name applied to nomadic hunting tribes in Quebec and Ontario, and later to the entire Algonquian linguistic family to which they belong. Located originally near Ottawa, the Algonquian tribe was driven northward by 17th-century wars with the Iroquois and British, whom they, as allies of the French, opposed. They had the characteristic attributes of a Plains tribe. The linguistic family, whose primitive culture preceded those of the Mound Builders and Iroquois, included the Arapaho, Blackfoot, and Cheyenne of the northern Plains; the Ojibway, Cree, Shawnee, Delaware, Mohegan, Narragansett, and Pequot of the eastern U.S.; and tribes as far south as the Powhatan. Longfellow uses Algonquian legends in his poem on the Mohawk hero Hiawatha.

Subjects: Literature.

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Laurie Anderson

(b. 1947)

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(1947– )

American Performance artist, poet, and musician, born in Chicago, the daughter of a wealthy paint manufacturer. In 1967 she moved to New York, where she gained a BA in art history from Barnard College in 1969 and an MFA from Columbia University (where she trained in painting and sculpture) in 1972. She also studied privately with Sol LeWitt. In 1972 she gave her first performance piece, Automotive, an outdoor concert for car horns, and by 1976 was well known in the USA and Europe. Her performances include numerous audio and visual effects (including slide projection and films) combined with spoken and sung elements (she is a singer and violinist, and since 1974 has been making her own instruments, notably a modified violin with an internal loudspeaker). Her sense of humour and endearing stage presence have been much admired. Anderson's major work is United States, ‘an eight-hour opus of song, narrative and sleights of hand and eye’ (RoseLee Goldberg, Performance Art, 1988). It is in four parts, and was first performed complete in 1983 at the Brooklyn Academy of Music over two nights. A song from the show, ‘O Superman’, was released on record in 1981 and got to number 2 in the British singles' chart. Her first album, Big Science, was released in 1982. In 1997 she was director of the Meltdown Festival in London, an annual concert series that specializes in unusual musical events and collaborations.

Subjects: Art.

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22 November 2013

Hacking OIP Derangement Syndrome

Sophos’s Naked Security blog noted a little-reported aspect of the Healthcare.gov rollout—at least sixteen cyberattacks on the site from 6 to 8 November. It’s unclear whether there were more on other days.

In addition, Information Week reported on software programmed to overload the website. As distributed on right-wing websites, it says:

"This program continually displays alternate page of the ObamaCare website. It has no virus, Trojans, worms, or cookies. The purpose is to overload the ObamaCare website, to deny serivce [sic] to users and perhaps overload and crash the system," reads the program's grammar- and spelling-challenged "about" screen. "You can open as many copies of this program as you want. Each copy opens multiple links to the site."
The technology magazine goes on to say that the “Destroy Obama Care” tool isn’t well designed for its intended task, and therefore is less effective at slowing the federal website than the lack of cooperation from Republican state governments.

Opponents of health-insurance reform have also tried to attack the law by spreading false news. Most notoriously, on the day the website went live an anonymous person posted a long complaint from a “Will Sheehan” about suffering penalties, including loss of a driver’s license and garnished income, after trying to sign up. Politifact and other news sources showed how that story could not be true. But clearly someone had put a lot of time and imagination into concocting it.

These efforts to stop people who need health coverage from obtaining it seem akin to gluing shut the doors of a hospital, tearing down the signs to a soup kitchen, or pushing in front of poor kids at a school cafeteria. Who would do something that cruel? Only people with OIP Derangement Syndrome.

1 comment:

J. L. Bell said...

The Daily Kos highlighted a website from California Republicans designed to look like the state's official health-insurance connector but created to discourage people without insurance from participating in the system.