A dataset providing GP recorded chronic obstructive pulmonary disease rates. Chronic Obstructive Pulmonary Disease (COPD) is a serious long-term lung disease in which the flow of air into the lungs is gradually reduced by inflammation of the air passages and damage to the lung tissue. Chronic Bronchitis and emphysema are common types of COPD. Chronic Obstructive Pulmonary Disease (COPD) is the fifth biggest killer disease in the UK, killing approximately 25,000 people a year in England. Further information For more information on public health, please visit: http://www.leeds.gov.uk/phrc/Pages/default.aspx

This data shows premature deaths (Age under 75) from Respiratory Disease, numbers and rates by gender, as 3-year range.

Smoking is the major cause of chronic obstructive pulmonary disease (COPD), one of the major Respiratory diseases. COPD (which includes chronic bronchitis and emphysema) results in many hospital admissions. Respiratory diseases can also be caused by environmental factors (such as pollution, or housing conditions) and influenza. Respiratory disease mortality rates show a socio-economic gradient.

Directly Age-Standardised Rates (DASR) are shown in the data, where numbers are sufficient, so that death rates can be directly compared between areas. The DASR calculation applies Age-specific rates to a Standard (European) population to cancel out possible effects on crude rates due to different age structures among populations, thus enabling direct comparisons of rates.

A limitation on using mortalities as a proxy for prevalence of health conditions is that mortalities may give an incomplete view of health conditions in an area, as ill-health might not lead to premature death.

Data source: Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF) indicator 4.07i. This data is updated annually.

This dataset provides the directly age-standardised mortality rate from respiratory diseases in individuals under the age of 75. Respiratory diseases, including conditions such as chronic obstructive pulmonary disease (COPD), asthma, and pneumonia, are a major cause of premature death. This indicator supports the monitoring of respiratory health and the effectiveness of interventions aimed at reducing early mortality in the Birmingham and Solihull area.

Rationale Reducing premature mortality from respiratory diseases is a key objective in improving population health and reducing health inequalities. This indicator helps to track progress in respiratory disease prevention, early diagnosis, and management, and supports strategic planning and resource allocation.

Numerator The numerator is the number of deaths from respiratory diseases (ICD-10 codes J00–J99) registered in the respective calendar years, for individuals aged under 75.

Denominator The denominator is the population of individuals under 75 years of age, also aggregated into quinary age bands. For single-year rates, the population is based on the 2021 Census. For three-year rolling averages, the denominator is the aggregated population-years over the three years.

Caveats Data may not align with published Office for National Statistics (ONS) figures due to differences in postcode lookup versions and the application of comparability ratios used in Office for Health Improvement and Disparities (OHID) data.

External references Fingertips Public Health Profiles – Respiratory Disease Indicator

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

This data shows the percentage of adults (age 18 and over) who are current smokers. Smoking is the single biggest cause of preventable death and illnesses, and big inequalities exist between and within communities. Smoking is a major risk factor for many diseases, such as lung cancer, chronic obstructive pulmonary disease (COPD, bronchitis and emphysema) and heart disease. It is also associated with cancers in other organs. Smoking is a modifiable lifestyle risk factor. Preventing people from starting smoking is important in reducing the health harms and inequalities. This data is based on the Office for National Statistics (ONS) Annual Population Survey (APS). The percentage of adults is not age-standardised. In this dataset particularly at district level there may be inherent statistical uncertainty in some data values. Thus as with many other datasets, this data should be used together with other data and resources to obtain a fuller picture. Data source: Office for Health Improvement and Disparities (OHID) Public Health Outcomes Framework (PHOF) indicator 92443 (Number 15). This data is updated annually.

This dataset provides the percentage of patients diagnosed with chronic obstructive pulmonary disease (COPD) as recorded on general practice disease registers. It serves as a key indicator for understanding the burden of COPD within the population and supports efforts to monitor and manage respiratory health at the primary care level.

Rationale

COPD is a progressive respiratory condition that significantly impacts quality of life and healthcare resources. Monitoring its prevalence helps identify trends, allocate resources effectively, and evaluate the impact of public health interventions aimed at prevention, early diagnosis, and management. Reducing the prevalence of COPD is a public health priority.

Numerator

The numerator is the number of patients with a recorded diagnosis of COPD on the practice disease register.

Denominator

The denominator is the total number of patients registered with the practice (total practice list size).

Caveats

The accuracy of this indicator depends on the completeness and consistency of clinical coding within general practices. Variations in diagnostic practices or underdiagnosis may affect the reported prevalence. Additionally, the indicator does not account for disease severity or treatment outcomes.

External References

Further information is available on the Fingertips Public Health Profiles provided by the Office for Health Improvement and Disparities.

Localities ExplainedThis dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations:Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs).Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities.This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address.

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data was reported at 13.800 Ratio in 2016. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data is updated yearly, averaging 13.800 Ratio from Dec 2016 (Median) to 2016, with 1 observations. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: per 100,000 Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Health Statistics. Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

Years of Life Lost (YLL) as a result of death from bronchitis and emphysema, classified by underlying cause of death. Directly age-Standardised Rates (DSR) per 100,000 population Source: Office for National Statistics (ONS) Publisher: Information Centre (IC) - Clinical and Health Outcomes Knowledge Base Geographies: Local Authority District (LAD), Government Office Region (GOR), National, Strategic Health Authority (SHA) Geographic coverage: England Time coverage: 2005-07, 2007 Type of data: Administrative data

https://www.nature.com/articles/s41588-018-0321-7

Lung function is an important indicator of respiratory health and mortality. Measures of lung function show irreversible airway obstruction in chronic obstructive pulmonary disease (COPD), a progressive condition affecting 900,000 people in the UK. Smoking is a strong risk factor for COPD but not all smokers are equally susceptible. Genetic approaches to understanding the mechanisms underlying the maintenance of good lungs aim to reveal previously unknown molecular targets for drug development and to facilitate stratified approaches to treatment and care. This project aims to detect rare genetic variants associated with lung function. Once discovered, such variants tend to exert a large effect on disease risk and provide a means to translate findings from genetic studies of lung function to clinical relevant research and development. The proposed study leverages the power of Uk Biobank and respiratory genomics to advance understanding of lung function and COPD.

Directly standardised mortality rate from respiratory disease for people aged under 75, per 100,000 population. Purpose To ensure that the NHS is held to account for doing all that it can to prevent deaths from respiratory disease in people under 75. Current version updated: Feb-17 Next version due: Nov-17

Survival estimates for adults diagnosed with cancer, by stage, for years 2012, 2013, 2014 and 2015, England

The dataset contains socio-demographic characteristics of chronic respiratory disease patients (participants) along with their disease diagnosis, history related to their disease, health behavior and risk factors, variables related to the constructs of theory of planned behaviour and health belief model all of which were incorporated into an evaluation questionnaire delivered to the participants at baseline and at end-line. It has data collected from the participants through St. Georges Respiratory Questionnaire (SGRQ), Test of adherence to Inhalers (TAI) and clinical assessment and review forms. The data are related health behaviour and clinical outcomes of such participants.

Chronic Health Condition Prevalence in Stockport, UK, 2016

Counts of Hypertension, Anxiety, Diabetes and Other Chronic Health Conditions

By data.world's Admin [source]

About this dataset

This dataset contains crucial information regarding the prevalence of various health conditions affecting Stockport, UK, in June 2016. This dataset will help you better understand the prevalence rates of Hypertension, Anxiety, Depression, Asthma, Obesity, Diabetes, Coronary Heart Disease (CHD), Falls (both accidental and medical-related), Cancer (various forms listed), Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD) , Stroke/Trans-Ischaemic Attack and Atrial Fibrillation amongst individuals living in Lower Layer Super Output Areas across Stockport which are grouped by codes. The count of individuals affected by each condition cited is provided along with the GP Registered Population for each LSOA which typically ranges from 1000 to 2000 people per LSOA. This data could be utilized to identify areas most impacted by healthcare related issues from a geographical perspective as well as help provide insight into chronic illnesses that may require further attention throughout Stockport's communities

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How to use the dataset

The data contained in this dataset consists of information on chronic health conditions gathered from Lower Layer Super Output Areas (LSOA) located in Stockport, UK for June 2016. The count information provided pertains to Hypertension, Anxiety, Depression, Asthma, Obesity, Diabetes, Coronary Heart Disease (CHD), Falls, Cancer and Chronic Kidney Disease (CKD), Chronic Obstructive Pulmonary Disease (COPD), Stroke/Trans-Ischaemic Attack and Atrial Fibrillation.

• To get a better understanding of what this dataset looks like we will start by reviewing the columns it contains. The columns contain information about: Lower Layer Super Output Area Code(lsoa11cd), Lower Layer Super Output Area Name(lsoa11nm & lsoa11nmw for Welsh language version) , GP Registered Population(GPRegPop), Hypertension (Hypertens), Anxiety(Anxiety), Depression(Depression) ect .

• To get an overview of what this dataset is about use a summary statistic tool such as mean(), median(), mode() etc to aggregate your data. This can be done by computing each column’s summary statistics separately or by combining them into one table for every condition listed here. This way you can obtain an overview which accurately reflects the overall population distribution pertaining to particular chronic health condition across multiple LSOA's at one time frame only.

• For deeper analysis refine your finding further or delve down into cause and effect make use graphs & charts such as scatter plots or line charts etc,. as well correlational analysis such Joint Analysis/Common Factor Analysis & Multiple Regression Analysis which will give you an insight into co-occurrence frequency or other related variables whcih could play a role in any particular health condition cause and affect outcomes over a period of time allowing further investigation if needed be pertaining suspected underlying causes regarding chronic medical conditions observed .

• Finally it is important that comprehensive datasets are created using wide range factors relevant local determinants before drawing conclusions so allow public bodies with decision making power make informed decisions accordingly when devising strategies for tackling causes associated with specific chronic medical coniditons target population groups required provide assistance towards public welfare goal become more efficient targeting

Research Ideas

• Analyzing the geographic variation of health conditions in Stockport in order to inform public health policy decisions. For example, to identify areas where specific interventions are needed to improve healthcare outcomes, or target resources at particular (at-risk) populations.
• Examining the correlations between different health conditions and identifying potential links or risk factors for developing one condition when another is present.
• Utilizing the GP registered population for each LSOA as a metric for predicting which areas of Stockport are likely to require additional funds or resources in order ensure adequate access to healthcare services for their residents

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more informat...

United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data was reported at 17.000 NA in 2016. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data is updated yearly, averaging 17.000 NA from Dec 2016 (Median) to 2016, with 1 observations. United Kingdom UK: Mortality Rate Attributed to Household and Ambient Air Pollution: Age-standardized: Male data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United Kingdom – Table UK.World Bank.WDI: Health Statistics. Mortality rate attributed to household and ambient air pollution is the number of deaths attributable to the joint effects of household and ambient air pollution in a year per 100,000 population. The rates are age-standardized. Following diseases are taken into account: acute respiratory infections (estimated for all ages); cerebrovascular diseases in adults (estimated above 25 years); ischaemic heart diseases in adults (estimated above 25 years); chronic obstructive pulmonary disease in adults (estimated above 25 years); and lung cancer in adults (estimated above 25 years).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

BackgroundPeople with Cystic Fibrosis (CF) in the UK and elsewhere are increasingly surviving into adulthood, yet there is little research on the employment consequences of having CF. We investigated, for the first time in a UK-wide cohort, longitudinal employment status, and its association with deprivation, disease severity, and time in hospital.MethodsWe did a longitudinal registry study of adults with CF in the UK aged 20 to 40 (3458 people with 15,572 observations between 1996 and 2010), using mixed effects models.ResultsAround 50% of adults with CF were in employment. Male sex, higher lung function and body mass index, and less time in hospital were associated with improved employment chances. All other things being equal, being in the most deprived quintile was associated with a reduction of employment prevalence of 17.6 percentage points compared to the prevalence in the least deprived quintile. Having poor lung function was associated with a reduced employment prevalence of 7.2 percentage points compared to the prevalence for people with relatively good lung function. Acting synergistically, deprivation modifies the effect of lung function on employment chances – poor lung function in the least deprived group was associated with a 3 percentage point reduction in employment chances, while poor lung function in the most deprived quintile was associated with a 7.7 point reduction in employment chances.ConclusionsGreater deprivation, disease severity, and time in hospital are all associated with employment chances in adults with CF. Furthermore, our analysis suggests that deprivation amplifies the harmful association of disease severity on employment. Future studies should focus on understanding and mitigating the barriers to employment faced by people with CF.

Rates of mortality involving cancers, cardiovascular diseases, chronic kidney disease, dementia, diabetes, and respiratory diseases, by Census 2021 variables. Experimental Statistics.

United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data was reported at 10.900 % in 2016. This records a decrease from the previous number of 11.200 % for 2015. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data is updated yearly, averaging 12.200 % from Dec 2000 (Median) to 2016, with 5 observations. The data reached an all-time high of 16.400 % in 2000 and a record low of 10.900 % in 2016. United Kingdom UK: Mortality from CVD, Cancer, Diabetes or CRD between Exact Ages 30 and 70 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s UK – Table UK.World Bank: Health Statistics. Mortality from CVD, cancer, diabetes or CRD is the percent of 30-year-old-people who would die before their 70th birthday from any of cardiovascular disease, cancer, diabetes, or chronic respiratory disease, assuming that s/he would experience current mortality rates at every age and s/he would not die from any other cause of death (e.g., injuries or HIV/AIDS).; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted Average;

Background. Chronic obstructive pulmonary disease (COPD) is a debilitating lung condition characterised by progressive lung function limitation. COPD is an umbrella term and encompasses a spectrum of pathophysiologies including chronic bronchitis, small airways disease and emphysema. COPD caused an estimated 3 million deaths worldwide in 2016, and is estimated to be the third leading cause of death worldwide. The British Lung Foundation (BLF) estimates that the disease costs the NHS around £1.9 billion per year. COPD is therefore a significant public health challenge. This dataset explores the impact of hospitalisation in patients with COPD during the COVID pandemic.

PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. There are particularly high rates of physical inactivity, obesity, smoking & diabetes. The West Midlands has a high prevalence of COPD, reflecting the high rates of smoking and industrial exposure. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS.

EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Scope: All hospitalised patients admitted to UHB during the COVID-19 pandemic first wave, curated to focus on COPD. Longitudinal & individually linked, so that the preceding & subsequent health journey can be mapped & healthcare utilisation prior to & after admission understood. The dataset includes ICD-10 & SNOMED-CT codes pertaining to COPD and COPD exacerbations, as well as all co-morbid conditions. Serial, structured data pertaining to process of care (timings, staff grades, specialty review, wards), presenting complaint, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, nebulisers, antibiotics, inotropes, vasopressors, organ support), all outcomes. Linked images available (radiographs, CT).

Available supplementary data: More extensive data including wave 2 patients in non-OMOP form. Ambulance, 111, 999 data, synthetic data.

Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

Disability in activities of daily living (ADL) is a common unmet need among people with advanced respiratory disease. Rehabilitation could help prolong independence, but indicators for timely intervention in this population are lacking. This study aimed to identify trajectories of disability in ADLs over time, and predicting factors, in advanced respiratory disease. Multi-site prospective cohort study in people with advanced non-small cell lung cancer (NSCLC), chronic obstructive pulmonary disease (COPD) or interstitial lung disease (ILD), recruited from hospital or community services, throughout England. Disability in basic (Barthel Index) and instrumental (Lawton–Brody IADL Scale) ADLs were assessed monthly over six months. Visual graphical analysis determined individual trajectories. Multivariate logistic regression examined predictors of increasing disability in basic and instrumental ADLs. Between March 2020 and January 2021, we recruited participants with a diagnosis of NSCLC (n = 110), COPD (n = 72), and ILD (n = 19). 151 participants completed ≥3 timepoints and were included in the longitudinal analysis. Mobility limitation was an independent predictor of increasing disability in instrumental ADLs (odds ratio, 1⋅41 [CI: 1⋅14–1⋅74], p = 0⋅002). Mobility limitation could be used as a simple referral criterion across people with advanced respiratory disease to ensure timely rehabilitation that targets independence in ADLs. To our knowledge this is the first prospective cohort study of trajectories of disability in activities of daily living (ADL) in advanced respiratory disease, including recruitment during the Covid-19 pandemic.It adds to existing evidence by identifying individual variability in trajectories of ADL disability which are undetected at group level.The identification of mobility limitation as a predictor of increasing ADL disability, while controlling for malignant or non-malignant respiratory disease, is novel and has practical utility.Our findings have implications for clinical care, as early identification of functional decline through use of mobility limitation tools could flag early referral to rehabilitation services, potentially preventing or delaying forthcoming functional decline and avoiding reactive crisis management.Mobility limitation is a predictor of increasing disability in activities of daily living in advanced disease, which could be used to flag early referral to rehabilitation services, to help prevent or delay forthcoming functional decline and avoid reactive crisis management To our knowledge this is the first prospective cohort study of trajectories of disability in activities of daily living (ADL) in advanced respiratory disease, including recruitment during the Covid-19 pandemic. It adds to existing evidence by identifying individual variability in trajectories of ADL disability which are undetected at group level. The identification of mobility limitation as a predictor of increasing ADL disability, while controlling for malignant or non-malignant respiratory disease, is novel and has practical utility. Our findings have implications for clinical care, as early identification of functional decline through use of mobility limitation tools could flag early referral to rehabilitation services, potentially preventing or delaying forthcoming functional decline and avoiding reactive crisis management. Mobility limitation is a predictor of increasing disability in activities of daily living in advanced disease, which could be used to flag early referral to rehabilitation services, to help prevent or delay forthcoming functional decline and avoid reactive crisis management

There is increasing interest in care pathways for acute exacerbations of disease, which are safe but avoid hospital admission. A virtual ward is a system where people who may otherwise be admitted to hospital receive hospital-led care in their home with observations and reviews conducted remotely by a specialist team. A virtual ward for COPD exacerbations has been recommended by NHS England, promoted following a rapid evaluation report published in 2022 and a number of small studies. To support the evaluation of this new service, PIONEER has developed a highly granular dataset of 6,973 Respiratory Virtual Ward admissions. The data includes demography, serial physiology, assessments, diagnostic codes (ICD-10 & SNOMED-CT), initial presentation, presenting symptoms, Imaging, Prescriptions, Ward locations and outcomes including mortality, readmissions and out patient follow up. The current dataset includes admissions from January 2019 to December 2023.

Geography: The West Midlands (WM) has a population of 6 million & includes a diverse ethnic & socio-economic mix. UHB is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & > 120 ITU bed capacity. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”.

Data set availability: Data access is available via the PIONEER Hub for projects which will benefit the public or patients. This can be by developing a new understanding of disease, by providing insights into how to improve care, or by developing new models, tools, treatments, or care processes. Data access can be provided to NHS, academic, commercial, policy and third sector organisations. Applications from SMEs are welcome. There is a single data access process, with public oversight provided by our public review committee, the Data Trust Committee. Contact pioneer@uhb.nhs.uk or visit www.pioneerdatahub.co.uk for more details.

Available supplementary data: Matched controls; ambulance and community data. Unstructured data (images). We can provide the dataset in OMOP and other common data models and can build synthetic data to meet bespoke requirements.

Available supplementary support: Analytics, model build, validation & refinement; A.I. support. Data partner support for ETL (extract, transform & load) processes. Bespoke and “off the shelf” Trusted Research Environment (TRE) build and run. Consultancy with clinical, patient & end-user and purchaser access/ support. Support for regulatory requirements. Cohort discovery. Data-driven trials and “fast screen” services to assess population size.

Supplementary files for article "Understanding the lived experience of idiopathic pulmonary fibrosis and how this shapes views on home-based pulmonary rehabilitation in Delhi, India"Objectives: Pulmonary Rehabilitation (PR) is a high-impact intervention for individuals with idiopathic pulmonary fibrosis (IPF) but access is limited in India. PR barriers include distance to travel, lack of service provision and lack of healthcare professionals to deliver PR, thus it is disproportionate to the immense burden of IPF in India. We explored the lived experiences of people living with IPF, family caregivers (CGs) and healthcare workers (HCWs) as well as their views towards home-based PR (HBPR) in Delhi, India.Methods: A qualitative study using semi-structured interviews with individuals with IPF (n = 20), CGs (n = 10) and HCWs (n = 10) was conducted. Data were analysed using codebook thematic analysis.Results: Three major themes were generated: (i) Health impact, which included pathophysiological changes, range of symptoms experienced, disease consequences and impact of comorbidities; (ii) Disease management, which described strategies to control the progression and overall management of IPF, such as medications and exercises; (iii) Mode of Pulmonary Rehabilitation, which described perceptions regarding HBPR, comparisons with centre-based programmes, and how HBPR may fit as part of a menu of PR delivery options.Conclusion: People living with IPF, family caregivers and healthcare workers were positive about the potential implementation of HBPR and suggested the development of a paper-based manual to facilitate HBPR over digital/online approaches. The content of HBPR should be sensitive to the additional impact of non-IPF health issues and challenges of reduced interactions with healthcare professionals.©The Author(s) CC BY 4.0