Descriptive statistics: - Measures of tendency: mean; mode; median; empirical quantile of order p (0<p<1);

- Measures of dispersion: variance; standard deviation; interquartile range; range;

- Measures of shape: skewness; kurtosis. Outliers (moderate and extreme).

Visualising data distribution: histogram (continuous data); box-plot; stem-and-leaf (rarely used in practical applications).

Hypothesis testing:- An introduction;

- Basic definitions: the meaning of a hypothesis in the statistical context; formulating a hypothesis test: the null hypothesis versus the alternative hypothesis, unilateral and bilateral tests; test statistic; rejection region; p-value;

- The analogy between the philosophy underlying hypothesis testing and the framework of the criminal trial;

- Different types of errors: type I error; type II error. The power of a test.

An outline on how to conduct a hypothesis test (one population), with emphasis on the large-sample test and t-tests.

Defining outcome in health.

 
Different types of PRO instruments. Type of measurement scale in health questionnaires: nominal; ordinal; interval; ratio. Different types of response scales. When to apply each of them.

Analysing some well-known health questionnaires to measure: health-related quality of life, and wellbeing. Health-related quality of life: the 36-Item Short Form Survey, SF-36 as well as its shorter versions, SF-12, SF-6. The EQ-5D instruments: EQ-5D-3L, EQ-5D-5L, EQ-5D-5Y (for children). Advantages and disadvantages of each questionnaire were discussed in the class. In regard to the wellbeing, the World Health Organization Wellbeing Index (WHO-5) was analysed.

Evaluation of a PRO instrument: validity; reliability; content validity; construct validity; criterion validity; test-retest or intra-interviewer reliability; internal consistency; inter interviewer variability.

Starting the statistical analysis of health questionnaires.

Introduction to the questionnaire: "Evaluating risk for cardiovascular diseases in the Portuguese population". Analysing the wording of the questions as well as the scale used in each question. Afterwards, students started the analysis of the respective database. Exploratory data analysis (an introduction). The analyses were developed with the spreadsheet Microsoft Excel and IBM SPSS Software.

The controversy over the calculation of DALY and QALY to support health policy decision-making. An overview of some European health agencies about this issue, as for instance: ECHOUTCOME (European consortium in healthcare outcomes and cost-benefit research, FP7–Health project).

 
The shift in the paradigm of the organisation of the healthcare systems: the Patient-Centred Care approach. What does it mean? Definition by the World Health Organization (WHO). The roots of this term, which dates back to 1988.

Watching and analysing two documentary films released by:

- WHO (May 2017): What is people-centred care?

- The International Consortium for Health Outcomes Measurement (ICHOM): Measured Outcomes (2017) - A future view of value-based healthcare. An introduction to the ICHOM, focusing on the ICHOM Standard Sets.

Patient-Reported Outcomes (PROM), or Patient-Reported Outcome Measures (PROMS): an instrument to evaluate health care systems. The health questionnaires. What should be measured with this type of instrument from the patient's perspective?

Defining Quality of Life (in a broad sense) and Health-Related Quality of Life (HRQoL), and their determinants.

Determination of DALY (in practice):

- Presentation of the Portuguese Inpatient Database.

- Analysing Healthcare-Associated Infections (HAI) based on the Portuguese Inpatient Database. A detailed study of the DALY calculation for Clostridium Difficile Infection (CDI).

Pedro Tremoceiro (master student) presented the Excel spreadsheets for computing the DALY associated with HAI, giving special emphasis to CDI.