Latest news with #populationHealth
The Independent
04-07-2025
- Health
- The Independent
Healthy life expectancy at record low for women in most deprived areas
Females in the most deprived areas of England and Wales are likely to spend less than two thirds of their life in good health – the lowest figure since recent records began. The inequality gap between men and women has also grown, with those living in better-off parts of England enjoying around two more decades of healthy life. The Covid-19 pandemic, with its increased levels of mortality, is continuing to have an impact on life expectancy estimates, according to the Office for National Statistics (ONS) which published the figures. Females born between 2020 and 2022 in the most deprived areas of England were likely to spend just 65.1% of their lives in good health, compared with 81.5% in the least deprived areas, the ONS found. The estimate for the most deprived areas is the lowest since the time series began in 2013-15, when it stood at 66.3%. For males born in 2020-22, the proportion of life expected to be spent in good health was 70.4% for those in the most deprived areas and 84.5% for those in the least deprived. The figure for males in the most deprived parts of England is broadly unchanged on recent years. The gap in healthy life expectancy between females born in the most and least deprived areas has widened from 19.6 years in 2013-15 to 20.2 years in 2020-22, while for males it has grown from 18.7 to 19.1. Greg Ceely, ONS head of population health monitoring, said: 'The pandemic led to increased mortality, the impact of which is seen in our life expectancy estimates. 'However, not everyone was impacted equally. 'The biggest decline in life expectancy was seen in the most deprived areas. 'Healthy life expectancy also declined, and in England and Wales women in the most deprived areas were expected to spend the lowest proportion of life in 'good' health – the smallest since our records began.' Figures for Wales cannot be compared directly with England, due to different systems of measuring deprivation. But the proportion of life that females born in 2020-22 in the most deprived areas of Wales are likely to spend in good health, 61.5%, is the lowest since those estimates began in 2013-15. The equivalent figure for women born in the least deprived areas is 80.7%. For males in Wales, the proportions were 70.2% for the most deprived areas and 83.6% for the least deprived. Although the latest estimates represent a drop compared with the pre-pandemic period, this does not mean a baby born between 2020 and 2022 will necessarily go on to live a less healthy life. Improvements in mortality rates in the future would lead to increases in life expectancy estimates, the ONS noted.
Yahoo
04-07-2025
- Health
- Yahoo
Healthy life expectancy at record low for women in most deprived areas
Females in the most deprived areas of England and Wales are likely to spend less than two thirds of their life in good health – the lowest figure since recent records began. The inequality gap between men and women has also grown, with those living in better-off parts of England enjoying around two more decades of healthy life. The Covid-19 pandemic, with its increased levels of mortality, is continuing to have an impact on life expectancy estimates, according to the Office for National Statistics (ONS) which published the figures. Females born between 2020 and 2022 in the most deprived areas of England were likely to spend just 65.1% of their lives in good health, compared with 81.5% in the least deprived areas, the ONS found. The estimate for the most deprived areas is the lowest since the time series began in 2013-15, when it stood at 66.3%. For males born in 2020-22, the proportion of life expected to be spent in good health was 70.4% for those in the most deprived areas and 84.5% for those in the least deprived. The figure for males in the most deprived parts of England is broadly unchanged on recent years. The gap in healthy life expectancy between females born in the most and least deprived areas has widened from 19.6 years in 2013-15 to 20.2 years in 2020-22, while for males it has grown from 18.7 to 19.1. Greg Ceely, ONS head of population health monitoring, said: 'The pandemic led to increased mortality, the impact of which is seen in our life expectancy estimates. 'However, not everyone was impacted equally. 'The biggest decline in life expectancy was seen in the most deprived areas. 'Healthy life expectancy also declined, and in England and Wales women in the most deprived areas were expected to spend the lowest proportion of life in 'good' health – the smallest since our records began.' Figures for Wales cannot be compared directly with England, due to different systems of measuring deprivation. But the proportion of life that females born in 2020-22 in the most deprived areas of Wales are likely to spend in good health, 61.5%, is the lowest since those estimates began in 2013-15. The equivalent figure for women born in the least deprived areas is 80.7%. For males in Wales, the proportions were 70.2% for the most deprived areas and 83.6% for the least deprived. Although the latest estimates represent a drop compared with the pre-pandemic period, this does not mean a baby born between 2020 and 2022 will necessarily go on to live a less healthy life. Improvements in mortality rates in the future would lead to increases in life expectancy estimates, the ONS noted.
Forbes
18-06-2025
- Health
- Forbes
Data-Led Healthcare Transformation Depends On More Than Just Numbers
Asif Mujahid, Chief Data and Analytics Officer at Quartz Health Solutions. There is a saying that data alone doesn't change outcomes—trust does. As health plans and provider systems strive to modernize care delivery, improve population health and manage cost trends, the success of these efforts increasingly hinges on something less technical and more human: whether people trust the data they're given. We have seen the pattern too often: We deliver a thoughtfully designed dashboard. The metrics are right. The logic is sound. However, the reaction in the room isn't action—it's doubt. "Are these numbers right?" "That's not what we're seeing on the ground." "Can we trust this data?" This challenge isn't about technology. It's about trust. Until we solve for the trust factor, data-driven transformation will continue to underdeliver on its promise. The erosion of trust in data doesn't happen all at once—it accumulates slowly across multiple factors: • Data Quality: Inconsistent values, missing fields or outdated records fuel skepticism. • Interpretability By Audience: Technical teams may understand what an "impactable opportunity" or "risk-adjusted cost ratio" means, but front-line teams often don't. Thus, you are disenfranchising a segment of the audience from partaking in the benefits of using data. • Competing Truths: Health plans and providers frequently work from different systems and coding standards. When a physician's panel doesn't match the health plan's attribution list, both sides dig in—and mutual confidence erodes. • Lack Of Co-Ownership: When analytics are delivered to operational or clinical teams rather than built with them, people treat the outputs like surveillance rather than support. Now that we have established the problem statement, what does it take to rebuild trust in data? 1. Co-create the narrative. Involve clinicians, case managers, finance leads and operations to define which insights matter. Let them shape the use case, not just review the output. The more they help build the story, the more likely they are to believe it. 2. Validate in the open. Make data validation a collaborative process. Invite stakeholders to compare datasets, surface mismatches and resolve discrepancies together. 3. Explain, then recommend. Don't assume everyone understands PMPM, MLR, RAF or any other acronym we've come to normalize. Use plain language, and always connect the insight to an operational decision. ("What should we do differently because of this?") 4. Embed data in the workflow. Insights need to show up where decisions happen—not just in a dashboard but inside clinical notes, staffing huddles or care management prioritization. When data becomes part of daily operations, it gains legitimacy. 5. Measure trust as a metric. Start tracking how often reports are used, whether action plans stem from analytics and how confident your stakeholders feel in the data. Treat trust like a KPI, not an assumption. How do we know we've reached the promised land? We know we are doing something right when the conversation turns from whether something is right to what we can do about it. Health plan and provider teams align more easily on shared goals. Innovation takes root—not because the technology is better but because the belief in its value is stronger. In healthcare, data will never be perfect, but it can be trusted if we build that trust deliberately. That's the work ahead of us. Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?
