Health System Exam 1

What is a system?

A set of things that are interconnected in ways that result in the generation of identifiable behavioral patterns over time

How are systems categorized?

Inputs

Processes

Outputs

What is a healthcare system?

• Structured networks of public and private organizations and individuals

• Dedicated to providing

  • Access

  • Financing

  • Delivery of services

• With the primary purpose to

  • Promote

  • Restore

  • Maintain health

What are the four basic components of a healthcare system?

Financing

Insurance

Delivery

Payment

Financing

Collection of funding for healthcare

Insurance

• Protection against financial catastrophe by providing expensive healthcare when needed

• Determines package of health services the insured is entitled to

• Specifies how and where services may be received

Delivery

Provision of healthcare services by various providers

Payment

• The provision of reimbursement to providers for delivered services

  • Includes payment from insurers and cost-sharing from patients

Ways of organizing the components of healthcare systems

Levels of the healthcare system

Donabedian’s quality framework

Levels of the Health System

• Micro (care team - frontline care providers)

  • Healthcare professionals, family members, and others

• Meso (organization - infrastructure/resources)

  • Hospitals, clinics, nursing, homes, etc.

• Macro (environment - regulatory, market, and policy framework)

  • Public and private regulators, insurers, healthcare purchasers, research funders, et. al.

Donabedian’s Structure-Process-Outcome framework

1. Structure defines the environment where care processes happen

2. Process reflects the actions of care delivery

3. Outcome represents the effects of the care received

Four Basic Models of Healthcare

• Beveridge

• Bismarck

• National Health Insurance

• Out-of-Pocket

Beveridge

• Healthcare insurance is provided by the government

• Hospitals and clinics are government owned (typically)

(Ex. TRICARE, VA & IHS)

Bismarck

• Healthcare is financed by government and employers through payroll deductions

• Private/non-profit insurers must cover everyone

(Ex. Most working-age employed)

National Health Insurance

• Healthcare insurance is provided by the government

• Mix of public and private hospitals and clinics

• Providers are private sector

(Ex. Medicaid/Medicare)

Out-of-Pocket

• Patients pay directly for care

• No organized national system

(Uninsured)

Major characteristics of US Healthcare System

• No central agency governs the system

• Access to healthcare services is not uniform and is based on insurance coverage

• Imperfect market conditions lead to insurers not patients as purchasers of services

• Insurers act as intermediaries (middlemen) between financing and delivery of healthcare

• Existence of multiple payers (insurers)

Scientific Inquiry

The systematic process of asking questions and proposing explanations based on evidence acquired through validated methods

Objective Evidence Generation

Standardized approaches for conducting experiments and collecting data in a way that minimizes bias

Critical Evaluation of Information

Requires critical thinking skills to evaluate the quality of scientific information, identify credible sources, and understand the limitations of research findings

Distinguishing Credible Evidence

The ability to discern good quality evidence from misinformation or weak arguments, ensuring that decisions are based on robust science (instead of “belief”)

Promoting Best Practices

Provides the framework for finding, critiquing, and synthesizing that evidence to guide the development of best practice recommendations

The Five Fundamental Principles of Scientific Inquiry

• Order

• Inference

• Evaluation of probability

• Hypothesis testing

• Ethics

Order

• The scientific method is NOT “common sense”

• Arrives at conclusions through organized observation of entities or events classified on the basis of common properties and behaviors

  • Organizing by shared properties/behaviors allows for predictions (inference)

Inference and Chance

• Reasoning, or inference, means that a statement or conclusion ought to be accepted because the premise is true

• There is always the possibility conclusions are the result of chance

Two distinct approaches or arguments have evolved in the development of inferences:

• Deductive reasoning

• Inductive reasoning

Deductive Reasoning

• Minimizes “chance”

• Moves from the general to the specific

Inductive Reasoning

• Health research depends almost entirely on this

• Moves from the specific to the general

  • The conclusion does not necessarily follow from the premises or evidence (facts)

  • Increases the possibility that the premises may be true but the conclusion false

Evaluations of Probability

• Measures how likely an event, outcome, or result will occur

• Used to:

  • Test hypotheses

  • Determine how likely data patterns happened by random chance

• Measured from 0 to 1, where 0 is impossible and 1 is total clarity

Hypothesis Testing

• Carefully constructed predictions about characteristics of a population to answer a research question

• Includes independent variables (cause) and dependent variables (effect)

• Testing looks for differences in effects between groups exposed to the cause (or not)

• Testing requires:

  • Null hypothesis (H₀)

  • Alternative hypothesis (H_A)

Null hypothesis (H₀)

There is no difference between groups = failure to reject the null hypothesis

Alternative hypothesis (HA)

There is a difference and we can reject the null hypothesis

Ethics

• Ethics provide the moral societal standards for responsible research conduct

• These standards are based on respect, fairness, and well-being of research participants

Research Design

• Refers to the overall plan that allows researchers to seek answers to study questions and test study hypotheses

• Each design has inherent strengths and limitations that make some more appropriate to answer a research question over others

Important Concepts of Study Design

• Validity

  • Internal validity

  • External validity

• Variables

  • Independent

  • Dependent

  • Confounding

• Relationship among variables

  • Casuality

  • Correlation

• Function of time

  • Prospective analysis

  • Retrospective analysis

Validity

Reflects the accuracy of study results

Internal validity

the extent to which the design of the study is likely to produce reliable and consistent results pertaining to the relationship between the dependent variable and the independent variable

External validity

the extent to which the results of a study can be generalized to other settings

Variables

characteristics of a population (or sample) that are examined, measured, described, and interpreted

• vary from subject to subject over time

• main variables are classified as independent or dependent

  • independent variable is the cause

  • dependent variable is the effect

Confounding Variables

• variables (either unknown or known and uncontrolled) that have an association with both the independent and dependent variables

• confounders distort the true relationships between variables, leading to incorrect conclusions about causation

• risk of concluding a relationship exists when it doesn’t because of the nature of the confounding variable

Casuality

• a relationship between variables where one event (the cause) directly leads to another event (the effect)

• important to not that this relationship cannot be explained by a third event (confounder) this is known as spuriousness

Correlation

• a statistical concept that implies only that a relationship exists but has zero implications on causation

• there is not causation without correlation

• correlation does not imply causation

  • refers to the inability to legitimately deduce a cause-and-effect relationship between two events or variables solely on the basis of an observed association or correlation between them

Dimensions of Quality (STEEP)

• Safety

• Timeliness

• Efficiency

• Effectiveness

• Equity

• Person-centeredness

STEEEP - Safety

avoiding harm to patients from the care, treatment, and services that are intended to help them

STEEEP - Timeliness

reducing barriers to care, treatment, and services that may be caused by time delays, accessibility, or affordability

STEEEP - Efficiency

avoiding waste, including waste of all resources (human, equipment, supplies, finances, energy)

STEEEP - Effectiveness

avoiding overuse of inappropriate care, treatment, and services and underuse of effective care, treatment, and services

STEEEP - Equity

removing variation in the quality of care, treatment, and services that may be based on patient characteristics such as gender, ethnicity, race, or socioeconomic status

STEEEP - Person-centeredness

providing care, treatment, and services that are respectful of and responsive to individual preferences, needs, and values

Limitations of STEEEP

• STEEEP was focused on the use of care (micro level)

• determinants of health and the use of health care are external to the clinic/hospital

Drivers of Health

• health behaviors (30%)

  • tobacco use

  • diet and exercise

  • alcohol and drug use

  • sexual activity

• clinical care (20%)

  • access to care

  • quality of care

• physical environment (10%)

• social and economic environment (40%)

Triple Aim

• Improving population health

• Reducing costs and improving value

• Improving patient experience

Quadruple Aim

Triple Aim + improving care team wellbeing

Quintuple Aim

Quadruple Aim + advancing health equity

Roles of pharmacists in improving quality (micro)

pharmacists are able to predict and anticipate the likely effects of medications on patients and would be able to recognize an opportunity to improve quality of care

• medication expert

• prevent errors

• decrease costs

• decrease adverse medication/health outcomes

• med management

role of pharmacists in improving quality (macro)

• pharmacists are skilled at analyzing complex systems, particularly those that involve medication-related processes, such as ordering, dispensing, and administration

• pharmacists have a core knowledge of medications, including their adverse effects, interactions, proper dosing, and monitoring parameters

• of healthcare professionals, pharmacists typically have the broadest knowledge base regarding the entire medication management system and are considered to be an authoritative source

measuring quality

• drivers

• proxies

• flawed

• burdensome

• the best we have

types of health care quality measures

measures used to assess and compare the quality of health care organizations are classified as either a structure, process, or outcome measure

• structural measures

• process measures

• outcome measures

structural measures

relate to the capacity, systems, and processes to provide high-quality care

process measures

indicate what a provider does to maintain or improve health, either for healthy people or for those diagnosed with a health care condition; typically reflect generally accepted recommendations of clinical practice

outcome measures

reflect the impact of the health care service or intervention on the health status of patients; may seem to represent the “gold standard” in measuring quality, but an outcome is the result of numerous factors, many beyond the providers’ control

research designs with potential for determining causality can be broadly categorized into two types

observational and experimental designs

observational designs

• researcher has no control over subjects’ exposure

• the researcher merely observes the interplay of independent variable (drug exposure) with the dependent variable (outcome of interest)

experimental designs

• researcher has some or total control over subjects’ exposure

• the researcher controls the independent variable (treatment) that is likely to have an impact on the dependent variable (outcome)

research designs can be classified using different sets of criteria which includes:

• study purpose

• time orientation

• investigator orientation

• experimental setting

study purpose - descriptive

describe or summarize information about the diseases, events, or characteristics of study subjects without making any causal inferences

• who - refers to the demographic characteristics

• what - defines a phenomenon based on specific inclusion and exclusion criteria

• why - provides clues about the possible causal mechanism for further study

• when - the time period related to the occurrence of the phenomenon

• where - the place of occurrence

• so what - relates to information that could identify the importance of the issue to the community (public health)

often used to generate data for a hypothesis

study purpose - analytic

studies are aimed at understanding the relationship and/or causal mechanism that may exist between two or more variables

• can be experimental or observational

• often complex and resource intensive

• usefulness of these studies lies in their ability to test the relationship and causal pathways

time orientation - prospective

where the researcher collects the data after the study onset by following individuals over a period of time

• strength - define the research variables

• limitation - resource (time and cost) intensive

• all experimental designs and some observational designs are prospective designs

time orientation - retrospective

involves the evaluation of data for past events or existing data, such as medical records, to achieve the research objective

• strength: less resource intensive using existing data or past events

• limitation: no control over the variables used, how they are defined, or how collected

investigator orientation

• based on the role played by the investigator in relation to control of the independent variables of interest (i.e. control over treatment exposure/randomization)

• based on the investigator’s orientation toward interventions, the research designs may be classified as:

  • experimental

  • quasi-experimental

  • observational studies

investigator orientation - experimental studies

investigators assign participants to intervention/treatment groups based on randomization or other methods of selection

• have the provide strongest causalty

• ex. randomized controlled trials

investigator orientation - quasi-experimental studies

investigators assign participants to intervention/treatment groups without the ability to randomize

• provide weaker causality than experimental and more than observational studies

• ex. nonequivalent groups, pretest-posttest, interrupted time series

investigator orientation - observational studies

investigators do not assign participants to groups and rely on pre-existing differences; they observe the natural course of events without influence

• have higher external validity

• ex. case control studies, cohort studies

quantitative data

• involve numerical or countable information to study research phenomenon

• are based on the philosophy of positivism which states that all information derived from sensory experience should be empirical evidence

• simply put, it explores “what is?”

qualitative data

• involve words or textual information

• are based on the philosophy of constructivism which states that the phenomenon of interest is socially constructed and therefore subject to multiple realities or interpretations

• simply put, it explores “how or why is?”

mixed methods

involve both quantitative and qualitative data

hierarchy of evidence (from most rigorous to least)

1. systematic reviews and meta-analyses

2. randomized controlled trials

3. cohort studies

4. case-controlled studies

5. case series and reports

6. background info and expert opinion

the most commonly used experimental design

randomized controlled trial (RCT)

the commonly used observational designs in clinical research

• cohort

• case control

• cross-sectional

• case series

• case reports

randomized controlled trials (RCT)

• considered to be the gold standard in evaluating the safety and efficacy of an intervention

• an experiment that involves randomization of intervention(s) to two or more groups

two elements of RCTs

1. randomization of study participants

2. always prospective

interventional group

the group in which participants are provided an intervention (also called “experimental” or “treatment” group)

control group

the group that is provided conventional or no intervention

what is the primary reason that contributes to RCTs being the strongest research design?

randomization

randomization

• increases internal validity of RCTs

  • any difference observed in clinical outcomes between the two groups could be causally attributed to study intervention

• the even distribution of all observed as well as unobserved baseline characteristics among the experimental and control groups alleviates any systematic differences among participants in influencing study results

allocation concealment

(randomization before enrollment)

What:

• preventing investigators from knowing which group a subject will be allocated to at the time of recruitment/enrollment in trial

• accomplished with central randomization or sealed envelopes

Why:

• reduces potential for selection bias in the study sample

  • knowing which group a subject will be assigned to may lead an investigator to choose not to enroll a subject

blinding

(randomization after enrollment)

What:

• preventing patients, investigators, and/or data analysts from being aware of treatment received during study and analysis of results

  • patients/investigators: use placebos and/or sham procedures to blind

  • data analysts: use coded data for analysis to mask treatment group

Why:

• prevent knowledge of treatment assignment from influencing use of other interventions, reporting of results, or analysis choices

open-label

NOBODY is blinded

treatment/group assignment is known to participants and investigators

single-blind

EITHER participants OR investigators are unaware of treatment/group assignment

double-blind

BOTH participants AND investigators are unaware of treatment/group assignments

triple-blind

EVERYONE is blinded, including participants, investigators, data analysts

controls

What:

• a comparator designed to account for errors and variability in the experimental design and measuring tools

  • placebo control

  • active control

  • historical control

Why:

• to ensure unbiased and objective observation and measurement of the effects of the study intervention on the outcome; accounts for “placebo effect” from non-study-related variables

placebo control

a matching, inactive treatment (“dummy”)

active control

an active intervention with known effects to which the study intervention can be compared, especially when non-treatment is unethical

historical control

comparing the study population at two different time points, such as pre- and post-intervention

95% confidence interval (CI)

a range of values that, if the sampling process were repeated many times, would contain the true population parameter 95% of the time

• it measures the prceision of the estimate

  • narrow intervals indiate greater precision

  • wider intervals indicate more uncertainty

• implies that there’s a 5% chance the generated interval will not contain the true value

dot-and-whiskers plot

a visual of a statistical value (dot) and the corresponding confidence interval (whiskers)

dot

represents the estimated value (coefficient)

whiskers

• a range of plausible values (95% confidence interval)

  • the whiskers define the plausible range for the true value of the quantity being estimated

• precision

  • shorter whiskers indicate that the estimate is more precise, while longer whiskers suggest greater uncertainty

• statistical significance

  • in plots where non-overlapping intervals suggest a significant difference, this interval is crucial for interpreting results

types of RCTs

• superiority

• equivalence

• non-inferiority

superiority study

investigators attempt to show an intervention is better than a comparator (control)

(traditional comparative trial used in most placebo-controlled RCTs)