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EpiCast Report: Heart Failure-Epidemiology Forecasts to 2026

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EpiCast Report: Heart Failure-Epidemiology Forecasts to 2026

Summary

Heart failure (HF), also referred to as congestive cardiac failure, is a heterogeneous condition in which the heart is unable to pump out sufficient blood to meet the metabolic needs of the body. Eventually, without the heart's pumping action to deliver oxygen and nutrient-rich blood to the cells, fatigue, shortness of breath, and coughing results. Even everyday activities such as walking, climbing stairs, or carrying weight can become tedious.

To forecast the diagnosed incident cases of HF and diagnosed prevalent cases of chronic HF (CHF) in the 7MM, GlobalData epidemiologists selected the best available nationally representative data ascertained through an exhaustive literature search.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of HF will increase from 1,990,569 cases in 2016 to 2,468,827 cases in 2026 at an annual growth rate (AGR) of 2.40%. The US had the highest number of diagnosed incident cases of HF in the 7MM in both 2016 and 2026, at 827,525 cases in 2016, and 1,081,878 cases in 2026.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of chronic HF (CHF) will increase from 14,403,423 cases in 2016 to 17,127,297 cases in 2026 at an AGR of 1.89%. The US had the highest number of diagnosed prevalent cases of CHF in the 7MM in both 2016 and 2026, at 5,816,242 cases in 2016, and 7,115,415 cases in 2026.

Scope

The Heart Failure (HF) EpiCast Report provides an overview of the risk factors and global trends of HF in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the diagnosed incident cases of HF, diagnosed incident cases of HF segmented by ejection fraction and ventricular dysfunction, acute HF hospitalizations, acute HF hospitalizations by worsening HF, advanced HF, and de novo HF, and acute HF hospitalization by patients admitted and discharged, hospital length of stay for acute HF hospitalization, diagnosed prevalent cases of chronic HF (CHF), and diagnosed prevalent cases of CHF segmented by ejection fraction. The diagnosed prevalent cases of CHF, CHF with REF, and CHF with PEF are further classified according to the New York Heart Association (NYHA) functional classes I-IV. The diagnosed incident cases of HF and diagnosed prevalent cases of CHF are segmented by age (at 10-year intervals, for ages 45 years and older) and sex.

The HF epidemiology report is written and developed by Masters- and PhD-level epidemiologists.

The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.

Reasons to buy

The Heart Failure EpiCast report will allow you to

Develop business strategies by understanding the trends shaping and driving the global HF market.

Quantify patient populations in the global HF market to improve product design, pricing, and launch plans.

Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for HF therapeutics in each of the markets covered.

Understand HF cases patient distribution by ejection fraction and NYHA functional classes.

READ MORE

Table Of Content

Scope

1 Table of Contents

1 Table of Contents 2

1.1 List of Tables 4

1.2 List of Figures 4

2 Heart Failure: Executive Summary 5

2.1 Related Reports 8

2.2 Upcoming Reports 8

3 Epidemiology 9

3.1 Disease Background 9

3.2 Risk Factors and Comorbidities 10

3.3 Global and Historical Trends 11

3.4 Forecast Methodology 13

3.4.1 Sources 14

3.4.2 Forecast Assumptions and Methods 22

3.4.3 Diagnosed Incident Cases of HF by EF 25

3.4.4 Diagnosed Incident Cases of HF by Ventricular Dysfunction 26

3.4.5 Acute HF Hospitalizations 27

3.4.6 Hospital Length of Stay for Acute HF Hospitalization 28

3.4.7 Diagnosed Prevalent Cases of CHF 29

3.4.8 Diagnosed Prevalent Cases of CHF by EF 31

3.4.9 Diagnosed Prevalent Cases of CHF by NYHA Classes 32

3.5 Epidemiological Forecast for Heart Failure (2016-2026) 34

3.5.1 Diagnosed Incident Cases of HF 34

3.5.2 Age-Specific Diagnosed Incident Cases of HF 35

3.5.3 Sex-Specific Diagnosed Incident Cases of HF 36

3.5.4 Diagnosed Incident Cases of HF by EF 37

3.5.5 Diagnosed Incident Cases of HF by VD 38

3.5.6 Acute HF Hospitalizations 38

3.5.7 Hospital Length of Stay for Acute HF Hospitalization 41

3.5.8 Diagnosed Prevalent Cases of CHF 41

3.5.9 Age-Specific Diagnosed Prevalent Cases of CHF 42

3.5.10 Sex-Specific Diagnosed Prevalent Cases of CHF 43

3.5.11 Diagnosed Prevalent Cases of CHF by EF 44

3.5.12 Diagnosed Prevalent Cases of CHF by NYHA Class 45

3.6 Discussion 47

3.6.1 Epidemiological Forecast Insight 47

3.6.2 Limitations of Analysis 48

3.6.3 Strengths of Analysis 48

4 Appendix 49

4.1 Bibliography 49

4.2 About the Authors 54

4.2.1 Epidemiologist 54

4.2.2 Reviewers 54

4.2.3 Global Director of Therapy Analysis and Epidemiology 55

4.2.4 Global Head and EVP of Healthcare Operations and Strategy 55

4.3 About GlobalData 56

4.4 Contact Us 56

4.5 Disclaimer 56


List Of Figure

1.2 List of Figures

Figure 1: 7MM, Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, 2016 and 2026 6

Figure 2: 7MM, Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, 2016 and 2026 7

Figure 3: 7MM, Age-Standardized Diagnosed Incidence of HF (Cases per 100,000 Population), Men and Women, Ages ?45 Years, 2016 11

Figure 4: 7MM, Age-Standardized Diagnosed Prevalence of CHF (%), Men and Women, Ages ?45 Years, 2016 12

Figure 5: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF 14

Figure 6: 7MM, Sources Used and Not Used to Forecast Diagnosed Prevalent Cases of CHF 15

Figure 7: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by EF 16

Figure 8: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by EF 17

Figure 9: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by Ventricular Dysfunction 18

Figure 10: 7MM, Sources Used to Forecast Hospitalizations for Acute HF 19

Figure 11: 7MM, Sources Used to Forecast Hospitalizations for Acute HF by Worsening CHF, Advanced HF, and de novo 20

Figure 12: 7MM, Sources Used to Forecast Hospital Length of Stay for Acute HF Hospitalization 21

Figure 13: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by NYHA Class 22

Figure 14: 7MM, Age-Specific Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, N, 2016 35

Figure 15: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages ?45 Years, N, 2016 36

Figure 16: 7MM, Diagnosed Incident Cases of HF by EF, Both Sexes, Ages ?45 Years, N, 2016 37

Figure 17: 7MM, Diagnosed Incident Cases of HF by VD, Both Sexes, Ages ?45 Years, N, 2016 38

Figure 18: 7MM, Acute HF Hospitalizations, Both Sexes, Ages ?45 Years, N, 2016 to 2026 39

Figure 19: 7MM, Acute HF Hospitalizations by Patients Admitted and Discharged, Both Sexes, Ages ?45 Years, 2016 39

Figure 20: 7MM, Acute HF Hospitalizations by Worsening Chronic HF, Advanced HF, and De Novo HF, Both Sexes, Ages ?45 40

Figure 21: 7MM, Hospital Length of Stay for Acute HF Hospitalization, Both Sexes, Ages ?45 Years, N, 2016 41

Figure 22: 7MM, Age-Specific Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, 2016 42

Figure 23: 7MM, Sex-Specific Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, 2016 43

Figure 24: 7MM, Diagnosed Prevalent Cases of CHF by EF, Both Sexes, Ages ?45 Years, N, 2016 44

Figure 25: 7MM, Diagnosed Prevalent Cases of CHF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 45

Figure 26: 7MM, Diagnosed Prevalent Cases of CHF with REF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 46

Figure 27: 7MM, Diagnosed Prevalent Cases of CHF with PEF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 47


List Of Table

1.1 List of Tables

Table 1: Risk Factors and Comorbidities for HF 10

Table 2: NYHA Functional Classification for CHF (Classes I-IV). 13

Table 3: 7MM, Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, N, Selected Years 2016-2026 35

Table 4: 7MM, Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, Selected Years 2016-2026 42

Licence Rights

Single User License:
Report can be used by individual purchaser only

Site License:
Report can be shared by unlimited users within one corporate location, e.g. a regional office

Corporate User License: 
Report can be shared globally by unlimited users within the purchasing corporation e.g. all employees of a single company

Section Purchase

To know more information on Purchase by Section, please send a mail to support@kenresearch.com

EpiCast Report: Heart Failure-Epidemiology Forecasts to 2026

Summary

Heart failure (HF), also referred to as congestive cardiac failure, is a heterogeneous condition in which the heart is unable to pump out sufficient blood to meet the metabolic needs of the body. Eventually, without the heart's pumping action to deliver oxygen and nutrient-rich blood to the cells, fatigue, shortness of breath, and coughing results. Even everyday activities such as walking, climbing stairs, or carrying weight can become tedious.

To forecast the diagnosed incident cases of HF and diagnosed prevalent cases of chronic HF (CHF) in the 7MM, GlobalData epidemiologists selected the best available nationally representative data ascertained through an exhaustive literature search.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed incident cases of HF will increase from 1,990,569 cases in 2016 to 2,468,827 cases in 2026 at an annual growth rate (AGR) of 2.40%. The US had the highest number of diagnosed incident cases of HF in the 7MM in both 2016 and 2026, at 827,525 cases in 2016, and 1,081,878 cases in 2026.

In the 7MM, GlobalData epidemiologists forecast that the diagnosed prevalent cases of chronic HF (CHF) will increase from 14,403,423 cases in 2016 to 17,127,297 cases in 2026 at an AGR of 1.89%. The US had the highest number of diagnosed prevalent cases of CHF in the 7MM in both 2016 and 2026, at 5,816,242 cases in 2016, and 7,115,415 cases in 2026.

Scope

The Heart Failure (HF) EpiCast Report provides an overview of the risk factors and global trends of HF in the seven major markets (7MM: US, France, Germany, Italy, Spain, UK, and Japan). It includes a 10-year epidemiological forecast for the diagnosed incident cases of HF, diagnosed incident cases of HF segmented by ejection fraction and ventricular dysfunction, acute HF hospitalizations, acute HF hospitalizations by worsening HF, advanced HF, and de novo HF, and acute HF hospitalization by patients admitted and discharged, hospital length of stay for acute HF hospitalization, diagnosed prevalent cases of chronic HF (CHF), and diagnosed prevalent cases of CHF segmented by ejection fraction. The diagnosed prevalent cases of CHF, CHF with REF, and CHF with PEF are further classified according to the New York Heart Association (NYHA) functional classes I-IV. The diagnosed incident cases of HF and diagnosed prevalent cases of CHF are segmented by age (at 10-year intervals, for ages 45 years and older) and sex.

The HF epidemiology report is written and developed by Masters- and PhD-level epidemiologists.

The EpiCast Report is in-depth, high quality, transparent and market-driven, providing expert analysis of disease trends in the 7MM.

Reasons to buy

The Heart Failure EpiCast report will allow you to

Develop business strategies by understanding the trends shaping and driving the global HF market.

Quantify patient populations in the global HF market to improve product design, pricing, and launch plans.

Organize sales and marketing efforts by identifying the age groups and sex that present the best opportunities for HF therapeutics in each of the markets covered.

Understand HF cases patient distribution by ejection fraction and NYHA functional classes.

READ MORE

Scope

1 Table of Contents

1 Table of Contents 2

1.1 List of Tables 4

1.2 List of Figures 4

2 Heart Failure: Executive Summary 5

2.1 Related Reports 8

2.2 Upcoming Reports 8

3 Epidemiology 9

3.1 Disease Background 9

3.2 Risk Factors and Comorbidities 10

3.3 Global and Historical Trends 11

3.4 Forecast Methodology 13

3.4.1 Sources 14

3.4.2 Forecast Assumptions and Methods 22

3.4.3 Diagnosed Incident Cases of HF by EF 25

3.4.4 Diagnosed Incident Cases of HF by Ventricular Dysfunction 26

3.4.5 Acute HF Hospitalizations 27

3.4.6 Hospital Length of Stay for Acute HF Hospitalization 28

3.4.7 Diagnosed Prevalent Cases of CHF 29

3.4.8 Diagnosed Prevalent Cases of CHF by EF 31

3.4.9 Diagnosed Prevalent Cases of CHF by NYHA Classes 32

3.5 Epidemiological Forecast for Heart Failure (2016-2026) 34

3.5.1 Diagnosed Incident Cases of HF 34

3.5.2 Age-Specific Diagnosed Incident Cases of HF 35

3.5.3 Sex-Specific Diagnosed Incident Cases of HF 36

3.5.4 Diagnosed Incident Cases of HF by EF 37

3.5.5 Diagnosed Incident Cases of HF by VD 38

3.5.6 Acute HF Hospitalizations 38

3.5.7 Hospital Length of Stay for Acute HF Hospitalization 41

3.5.8 Diagnosed Prevalent Cases of CHF 41

3.5.9 Age-Specific Diagnosed Prevalent Cases of CHF 42

3.5.10 Sex-Specific Diagnosed Prevalent Cases of CHF 43

3.5.11 Diagnosed Prevalent Cases of CHF by EF 44

3.5.12 Diagnosed Prevalent Cases of CHF by NYHA Class 45

3.6 Discussion 47

3.6.1 Epidemiological Forecast Insight 47

3.6.2 Limitations of Analysis 48

3.6.3 Strengths of Analysis 48

4 Appendix 49

4.1 Bibliography 49

4.2 About the Authors 54

4.2.1 Epidemiologist 54

4.2.2 Reviewers 54

4.2.3 Global Director of Therapy Analysis and Epidemiology 55

4.2.4 Global Head and EVP of Healthcare Operations and Strategy 55

4.3 About GlobalData 56

4.4 Contact Us 56

4.5 Disclaimer 56


List Of Figure

1.2 List of Figures

Figure 1: 7MM, Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, 2016 and 2026 6

Figure 2: 7MM, Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, 2016 and 2026 7

Figure 3: 7MM, Age-Standardized Diagnosed Incidence of HF (Cases per 100,000 Population), Men and Women, Ages ?45 Years, 2016 11

Figure 4: 7MM, Age-Standardized Diagnosed Prevalence of CHF (%), Men and Women, Ages ?45 Years, 2016 12

Figure 5: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF 14

Figure 6: 7MM, Sources Used and Not Used to Forecast Diagnosed Prevalent Cases of CHF 15

Figure 7: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by EF 16

Figure 8: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by EF 17

Figure 9: 7MM, Sources Used to Forecast Diagnosed Incident Cases of HF by Ventricular Dysfunction 18

Figure 10: 7MM, Sources Used to Forecast Hospitalizations for Acute HF 19

Figure 11: 7MM, Sources Used to Forecast Hospitalizations for Acute HF by Worsening CHF, Advanced HF, and de novo 20

Figure 12: 7MM, Sources Used to Forecast Hospital Length of Stay for Acute HF Hospitalization 21

Figure 13: 7MM, Sources Used to Forecast Diagnosed Prevalent Cases of CHF by NYHA Class 22

Figure 14: 7MM, Age-Specific Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, N, 2016 35

Figure 15: 7MM, Sex-Specific Diagnosed Incident Cases of HF, Ages ?45 Years, N, 2016 36

Figure 16: 7MM, Diagnosed Incident Cases of HF by EF, Both Sexes, Ages ?45 Years, N, 2016 37

Figure 17: 7MM, Diagnosed Incident Cases of HF by VD, Both Sexes, Ages ?45 Years, N, 2016 38

Figure 18: 7MM, Acute HF Hospitalizations, Both Sexes, Ages ?45 Years, N, 2016 to 2026 39

Figure 19: 7MM, Acute HF Hospitalizations by Patients Admitted and Discharged, Both Sexes, Ages ?45 Years, 2016 39

Figure 20: 7MM, Acute HF Hospitalizations by Worsening Chronic HF, Advanced HF, and De Novo HF, Both Sexes, Ages ?45 40

Figure 21: 7MM, Hospital Length of Stay for Acute HF Hospitalization, Both Sexes, Ages ?45 Years, N, 2016 41

Figure 22: 7MM, Age-Specific Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, 2016 42

Figure 23: 7MM, Sex-Specific Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, 2016 43

Figure 24: 7MM, Diagnosed Prevalent Cases of CHF by EF, Both Sexes, Ages ?45 Years, N, 2016 44

Figure 25: 7MM, Diagnosed Prevalent Cases of CHF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 45

Figure 26: 7MM, Diagnosed Prevalent Cases of CHF with REF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 46

Figure 27: 7MM, Diagnosed Prevalent Cases of CHF with PEF by NYHA Class, Both Sexes, Ages ?45 Years, N, 2016 47


List Of Table

1.1 List of Tables

Table 1: Risk Factors and Comorbidities for HF 10

Table 2: NYHA Functional Classification for CHF (Classes I-IV). 13

Table 3: 7MM, Diagnosed Incident Cases of HF, Both Sexes, Ages ?45 Years, N, Selected Years 2016-2026 35

Table 4: 7MM, Diagnosed Prevalent Cases of CHF, Both Sexes, Ages ?45 Years, N, Selected Years 2016-2026 42

Single User License:
Report can be used by individual purchaser only

Site License:
Report can be shared by unlimited users within one corporate location, e.g. a regional office

Corporate User License: 
Report can be shared globally by unlimited users within the purchasing corporation e.g. all employees of a single company

To know more information on Purchase by Section, please send a mail to support@kenresearch.com