The use of Data Analytics In Healthcare Systems is becoming increasingly essential in modern medical practices. Data analytics helps in decision-making, enhancing patient care outcomes, and optimizing the use of healthcare resources. The growing amount of data generated in healthcare from electronic health records (EHRs), medical imaging, lab results, and wearable devices offers an opportunity to improve services and reduce costs.
In this post, we will introduce sample questions and practice materials targeted towards the Summarize Written Text section of the PTE Speaking and Writing test. These examples center around the theme of “Data Analytics in Healthcare Systems.” We will also provide insights into how to score well by analyzing sample answers.
Practice Summarize Written Text Questions
Below are several model summaries based on Data Analytics in Healthcare Systems in the format of the “Summarize Written Text” task of the PTE exam.
Sample Question 1:
Healthcare systems are generating vast amounts of data through various channels such as electronic health records, diagnostic tests, and wearable devices. By harnessing this data, healthcare providers can implement data analytics techniques to improve decision-making, enhance patient care, and optimize operational efficiency. For instance, predictive analytics can help anticipate patient outcomes and reduce hospital readmissions, while prescriptive analytics supports recommending the most effective treatments. Furthermore, data-driven insights help reduce healthcare costs by minimizing waste and helping providers target resources where they are most needed.
Summarize Written Text in one sentence. You have 10 minutes to complete this task.
Answer Sample 1: Band 79+
Data analytics in healthcare systems improves decision-making, enhances patient care, and optimizes operational efficiency by leveraging data from various channels like EHRs, while predictive and prescriptive analytics help anticipate outcomes and reduce readmissions, which in turn lowers overall costs.
Analysis:
- Content: Fully represents the original passage by mentioning key benefits like improved decision-making, patient care, resource optimization, predictive and prescriptive analytics, as well as cost reduction.
- Form: A single sentence under 75 words.
- Grammar: The structure is complex but coherent.
- Vocabulary: Words such as “leverage,” “optimize,” “efficiency,” and “readmissions” reflect an academic tone.
- Spelling: No spelling errors.
Answer Sample 2: Band 65–79
Using data from sources like EHRs and wearable devices, healthcare systems improve decision-making, treatment, and patient care, while predictive analytics helps foresee hospital outcomes and thereby reduce costs.
Analysis:
- Content: Covers most of the important information but misses mentioning prescriptive analytics.
- Form: Clearly one sentence.
- Grammar: Appropriate use of clauses, though the complexity is moderate.
- Vocabulary: Uses simpler words like “improve” and “foresee” but still maintains relevance.
- Spelling: No spelling errors.
Answer Sample 3: Band 50–64
Healthcare systems use data to improve patient care and reduce costs through decision-making and predictive analytics.
Analysis:
- Content: The core ideas are present but oversimplified, omitting elements like resource optimization and prescriptive analytics.
- Form: Correct form with one sentence.
- Grammar: Simple sentence structure with fewer linking elements.
- Vocabulary: Basic, lacks the technical depth seen in higher-band responses.
- Spelling: No errors.
Sample Question 2:
Data analytics is revolutionizing healthcare by enabling the prediction of patient outcomes, optimizing treatment plans, and helping in the management of chronic diseases. By analyzing historical data, healthcare providers can identify patterns that improve the diagnosis and treatment process. One of the critical benefits of predictive analytics is its ability to forecast potential outbreaks of diseases and prepare healthcare systems accordingly. In addition, by employing big data tools, healthcare providers can reduce inefficiencies and ultimately enhance patient satisfaction.
Summarize Written Text in one sentence. You have 10 minutes to complete this task.
Answer Sample 1: Band 79+
Data analytics revolutionizes healthcare by predicting patient outcomes, optimizing treatments, managing chronic diseases, forecasting disease outbreaks, and reducing inefficiencies, which improves patient satisfaction.
Analysis:
- Content: Captures all the key elements such as patient outcomes, treatment optimization, and outbreak forecasting.
- Form: One concise sentence.
- Grammar: Presents a variety of clauses, all fitting smoothly together.
- Vocabulary: Strong academic terms like “revolutionizes,” “forecast,” and “inefficiencies” are used well within context.
- Spelling: Accurate.
Answer Sample 2: Band 65–79
Data analytics helps healthcare by predicting outcomes, optimizing treatment and managing diseases, as well as reducing resource inefficiencies and improving patient care.
Analysis:
- Content: Covers key points but does not emphasize disease outbreaks.
- Form: One linked sentence.
- Grammar: Slightly simpler construction, but still grammatically correct.
- Vocabulary: Uses appropriate but less advanced terms such as “improving” and “helping.”
- Spelling: No mistakes.
Answer Sample 3: Band 50–64
Data helps hospitals predict patient health and improve care by reducing inefficiencies.
Analysis:
- Content: Contains only basic information, leaving out many important aspects like chronic disease management and outbreak forecasting.
- Form: The sentence is correct in structure.
- Grammar: Simple but clear sentence.
- Vocabulary: Very basic, lacking academic depth.
- Spelling: No errors.
Vocabulary and Grammar Focus
Here are 10 key vocabulary words from the text, along with their definitions and examples:
-
EHR (noun) [iː eɪtʃ ɑːr] – Electronic Health Record: A digital version of a patient’s paper chart.
Example: “Doctors use EHRs to track patient history more efficiently.” -
Predictive (adj) [prɪˈdɪktɪv] – Relating to the ability to predict future health outcomes based on data.
Example: “Predictive analytics helps forecast patient recovery times.” -
Prescriptive (adj) [prɪˈskrɪptɪv] – Providing recommendations or rules for treatment based on data.
Example: “Prescriptive analytics suggests the best course of action for treating chronic diseases.” -
Forecast (verb) [ˈfɔːrkæst] – To predict or estimate a future event.
Example: “Data analytics can forecast disease outbreaks.” -
Chronic (adj) [ˈkrɒnɪk] – Persistent or long-lasting in health-related contexts.
Example: “Chronic diseases like diabetes require ongoing management.” -
Optimize (verb) [ˈɒptɪmaɪz] – Make the best or most effective use.
Example: “Healthcare providers optimize treatments based on patient data.” -
Inefficiency (noun) [ˌɪnɪˈfɪʃənsi] – Inability to use time and resources effectively.
Example: “Data tools help eliminate inefficiencies in healthcare operations.” -
Outcome (noun) [ˈaʊtkʌm] – A possible or actual result of healthcare practices.
Example: “Improving patient outcomes is a top priority in data-driven healthcare.” -
Resources (noun) [rɪˈzɔːrsɪz] – Supplies and medical tools available for use in healthcare.
Example: “Efficient use of healthcare resources reduces the overall cost.” -
Satisfaction (noun) [ˌsætɪsˈfækʃən] – The fulfilment of patient expectations in care received.
Example: “Data analytics significantly increases patient satisfaction by improving services.”
Conclusion
Data analytics in healthcare systems is an important and recurring topic in the PTE exam. Mastering how to summarize complex texts efficiently will not only prepare you for the exam but also boost your overall language proficiency, especially when dealing with text on sophisticated topics like healthcare. Keep practicing with additional resources, such as our analysis on Artificial intelligence in medical research, to further enhance your skills. Remember, consistent practice is the key to success!
