Healthcare Performance Metrics

𝐒𝐮𝐩𝐞𝐫𝐯𝐢𝐬𝐨𝐫 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐬 𝐓𝐡𝐚𝐭 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦 𝐄𝐦𝐩𝐥𝐨𝐲𝐞𝐞 𝐇𝐞𝐚𝐥𝐭𝐡 New research from Japan reveals the powerful impact of supervisors who both talk the talk AND walk the walk when it comes to employee health. The key finding? Doing both matters most. 𝐓𝐡𝐞 𝐒𝐭𝐮𝐝𝐲: Researchers examined 11,484 employees across 12 large Japanese companies to understand how the way supervisors promote health impact employee well-being within corporate Health and Productivity Management (HPM) programs. 𝐊𝐞𝐲 𝐅𝐢𝐧𝐝𝐢𝐧𝐠𝐬: ➤ 𝐈𝐧𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐚𝐥𝐨𝐧𝐞 𝐡𝐚𝐬 𝐥𝐢𝐦𝐢𝐭𝐞𝐝 𝐢𝐦𝐩𝐚𝐜𝐭 - Supervisors who only communicate about health policies and programs showed minimal associations with employee health outcomes ➤ 𝐏𝐫𝐚𝐜𝐭𝐢𝐜𝐢𝐧𝐠 𝐚𝐥𝐨𝐧𝐞 𝐢𝐬 𝐜𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭𝐥𝐲 𝐛𝐞𝐧𝐞𝐟𝐢𝐜𝐢𝐚𝐥 - Supervisors who actively role model healthy behaviors showed positive associations with employee psychological distress, work engagement, and self-rated health The combination yields the best outcomes - Employees whose supervisors both informed AND practiced healthy behaviors had the most favorable results across all health measures ➤ 𝐒𝐢𝐠𝐧𝐢𝐟𝐢𝐜𝐚𝐧𝐭 𝐢𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧 𝐞𝐟𝐟𝐞𝐜𝐭𝐬- The study found that combining informing and practicing behaviors created synergistic effects beyond either behavior alone 𝐖𝐡𝐲 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫𝐬: Many workplace health programs focus on communication and policy. This research shows that supervisor role modeling is essential and that the combination of communication AND modeling creates the greatest impact. Leaders can't just tell employees to be healthy; they need to demonstrate healthy behaviors themselves. The message for organizations: Training supervisors to both communicate health initiatives AND actively practice healthy behaviors should be a priority in corporate health programs. Johns Hopkins Medicine offers leaders several opportunities to understand their role in supporting employee health and well-being. We also offer managers many opportunities to bring their team together for a well-being activity, which gives the implicit message that our health is important. If you want to learn more about the role of leadership engagement in building a healthy workplace culture, click here -> https://amzn.to/3bG1q1D How does your company get leaders involved with employee health and well-being? Citation: Mori, T., Nagata, T., Odagami, K., & Mori, K. (2026). Supervisors' health-promoting behaviors and employee health in corporate health and productivity management: A cross-sectional study of large Japanese companies. @_Journal of Occupational and Environmental Medicine, 68_(1), 9-14. #LeadershipDevelopment #CHRO #Management

If hospitals waited for peer-reviewed journals to justify every operational decision in maternal care, most cost-saving programs would never exist. At Duke University Health System, that reality drove a decision that few maternity units in the U.S. have ever made: integrating physical therapy directly into postpartum care. Duke added physical therapy to the maternity unit and extended care into the early postpartum period through telehealth as an 18-month implementation pilot focused on readmissions and cost containment. The justification did not come from a journal article. It came from internal implementation data. That data was shared publicly at the 2025 Combined Sections Meeting of the American Physical Therapy Association (APTA) by Lisa Massa, PT, CLT, program coordinator for Duke’s Women’s Health Physical Therapy Residency. Duke averages ~350 births per month. With baseline postpartum readmission rates around 1-2%, roughly 126 readmissions would be expected over 18 months. During the pilot period where inpatient physical therapy was added on the maternity unit in addition to early postpartum telehealth as a follow-up, only 6 patients were readmitted. With postpartum readmissions costing hospitals $5,000-$8,000 each, Duke calculated over $500,000 in avoided costs. Patient satisfaction scores followed, along with nursing support and leadership buy-in. The program expanded to a second Duke hospital. Today, only 118 maternity units in the U.S. offer occupational and physical therapy services during postpartum admission. Duke accounts for two. They did not wait for journals to catch up to implementation science and public transparency. Hospitals that operate at the level of Duke can’t wait for journal publication to address the avoidable cost and harm affecting maternal health. ~Dr. Rebeca Segraves

What if an Apple-built health game could make an entire nation move more, sleep better — and plausibly add years of life? That wasn’t a thought experiment. It was LumiHealth. Six years ago, I led the team at Apple that partnered with Singapore’s Health Promotion Board to turn daily health behaviors into a national game. Not just a wellness app or a pilot. A country-scale experiment in behavior change. Tim Cook once said: "If you zoom out into the future, and you look back, and you ask, 'What was Apple's greatest contribution to mankind?' It will be about health." LumiHealth tested that belief at real scale: 377,000 participants. 32.9 million workouts completed. Independent analysis suggesting sustained activity gains could reduce mortality risk by 3–13%. This wasn’t about badges or step counts. It was about incentives, systems design, and what happens when a government treats prevention like infrastructure. The program is now winding down, and I wanted to celebrate it and reflect on what building a national health game taught me — about motivation, habit formation, and why most digital health efforts still underestimate what’s possible when design, policy, and technology align. I wrote my reflections and the inside story in the link below in comments 👇

All-Cause Readmissions - the Mother of ACO Performance A couple of days ago, I shared a chart showing the potential opportunities if we could eliminate readmissions [1]. While achieving zero readmissions is practically impossible, even a small reduction can lead to significant savings. Yesterday, the Centers for Medicare & Medicaid Services released the Performance Year 2023 ACO REACH dataset. What's particularly interesting is that they included both the All-Cause Readmission (ACR) measure and the gross savings rate! Let's analyze what we see. The chart displays two performance years (PY22 on the left and PY23 on the right), with three types of DCEs color-coded: High Needs (red), New Entrants (green), and Standard (blue). The x-axis shows the ACR measure (log-transformed, where lower is better), and the y-axis represents the gross savings rate. Each dot represents an ACO. I'll pause here - what do you notice? There's a clear inverse relationship between ACR and savings rate! This relationship is particularly strong for High Needs and New Entrants, and it's becoming even more pronounced in PY23. Simply put: lower readmissions correlate with higher savings! It's rare to see such a strong relationship in healthcare performance research - I'm quite surprised by these findings myself. A few key observations: * The Standard model ACOs don't show a meaningful relationship. This might be because their readmission rates are already so low that further reduction is challenging (as evidenced by the blue dots clustering on the lower end of ACRs). Many of these ACOs have extensive experience in the ACO program, and their members tend to be healthier. The potential for ACR-related improvements may be largely exhausted. * Here's a crucial point: if we hadn't separated the data by model type, we would have observed a "positive relationship" between ACR and savings rate, since High Needs populations show both higher savings and higher ACRs. This could have led to completely opposite conclusions - highlighting why understanding the context behind the data is essential! What do you all think? What do you do to lower the readmission rate measure? [1] https://lnkd.in/eeugjHEt

I made 60k a year coordinating discharges, defending $48K a day in preventable cost. No new tech. No new program. Just closing loops everyone else ignores. A patient waits days for placement. The bed’s blocked. The team’s frustrated. The meter’s running. Every extra day costs $120–$200 in unreimbursed overhead. Multiply that by a few patients a week. That’s your variance report. Here’s what one behavioral health case manager can prevent in a day: Avoided inpatient day → ~$2,400 saved Out-of-network transfer stopped → ~$14,000 kept ED boarding avoided → ~$6,500 saved Readmission prevented → ~$2,000 gained Community coordination → ~$1,500 avoided cost Even if only half hit, ROI is 10× after salary. All tied to: Avoided inpatient/ED events Stars bonuses Network integrity It’s margin defense, not overhead. Behavioral health case management isn’t a pilot . It’s throughput control. Each discharge done right reopens a bed, prevents clawbacks, and protects ratings. Even at 6:1 ROI, a 10-person team defends $12–$15M a year. Few teams can say that. The next time someone calls case management “overhead,” remind them: it’s the only department quietly turning friction into revenue recovery.

The urgent care network's CEO was direct: "𝘞𝘦 𝘯𝘦𝘦𝘥 𝘵𝘰 𝘳𝘦𝘥𝘶𝘤𝘦 𝘤𝘰𝘴𝘵𝘴 𝘣𝘺 15% 𝘵𝘰 𝘴𝘶𝘳𝘷𝘪𝘷𝘦 𝘵𝘩𝘦 𝘮𝘢𝘳𝘬𝘦𝘵 𝘤𝘰𝘯𝘴𝘰𝘭𝘪𝘥𝘢𝘵𝘪𝘰𝘯, 𝘣𝘶𝘵 𝘸𝘦 𝘤𝘢𝘯'𝘵 𝘤𝘰𝘮𝘱𝘳𝘰𝘮𝘪𝘴𝘦 𝘱𝘢𝘵𝘪𝘦𝘯𝘵 𝘤𝘢𝘳𝘦." We recognized an opportunity to fundamentally rethink the organization's operating model through a technology-enabled transformation. 𝗧𝗵𝗲 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲: 𝗠𝘂𝗹𝘁𝗶-𝗗𝗶𝗺𝗲𝗻𝘀𝗶𝗼𝗻𝗮𝗹 𝗣𝗿𝗲𝘀𝘀𝘂𝗿𝗲  - Reimbursement compression from payers  - Increasing competition from retail healthcare providers  - Rising patient expectations for digital experiences The traditional approach would have been incremental: trim staff, reduce supply costs, chase marginal efficiencies to achieve an 𝟴-𝟭𝟬% 𝗰𝗼𝘀𝘁 𝗿𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻 while degrading patient experience. 𝗧𝗵𝗲 𝗕𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵: 𝗗𝗮𝘁𝗮-𝗗𝗿𝗶𝘃𝗲𝗻 𝗖𝗮𝗿𝗲 𝗥𝗲𝗱𝗲𝘀𝗶𝗴𝗻 We built a digital transformation strategy around three core capabilities: 𝟭. 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗙𝗹𝗼𝘄 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 We analyzed three years of visit data and created an AI-driven staffing model that predicted patient volume with 94% accuracy at hourly intervals. This allowed precise staffing aligned to actual demand rather than static scheduling. Impact: 18% reduction in labor costs while reducing average wait times by 12 minutes. 𝟮. 𝗩𝗶𝗿𝘁𝘂𝗮𝗹-𝗙𝗶𝗿𝘀𝘁 𝗖𝗮𝗿𝗲 𝗣𝗮𝘁𝗵𝘄𝗮𝘆𝘀 Rather than viewing telemedicine as a separate offering, we redesigned the entire care delivery model around a virtual-first architecture. Patients began with an AI-triaged digital intake, followed by a virtual provider assessment, and only then proceeded to in-person care if clinically necessary. Impact: 41% of cases were resolved without in-person visits, reducing facility costs while increasing patient satisfaction scores by 9 points. 𝟯. 𝗨𝗻𝗶𝗳𝗶𝗲𝗱 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 We consolidated fragmented clinical and operational data into a unified platform, giving providers real-time decision support integrated into their workflow rather than requiring separate analysis. Impact: 17% reduction in unnecessary tests and procedures, 28% decrease in prescription costs through more precise medication management. 𝗧𝗵𝗲 𝗥𝗲𝘀𝘂𝗹𝘁𝘀: 𝗕𝗲𝘆𝗼𝗻𝗱 𝗖𝗼𝘀𝘁 𝗥𝗲𝗱𝘂𝗰𝘁𝗶𝗼𝗻 The combined impact exceeded all expectations:  - 23% reduction in total care delivery costs  - Patient satisfaction improvement from 72nd to 89th percentile  - Clinical quality metrics improvement across 7 of 8 key measures  - Provider satisfaction scores increased by 14 points Rather than merely surviving market pressures, they established a new care delivery model that attracted acquisition interest at a multiple 2.4x higher than the industry average. 𝘋𝘪𝘴𝘤𝘭𝘢𝘪𝘮𝘦𝘳: 𝘝𝘪𝘦𝘸𝘴 𝘦𝘹𝘱𝘳𝘦𝘴𝘴𝘦𝘥 𝘢𝘳𝘦 𝘮𝘺 𝘰𝘸𝘯 𝘢𝘯𝘥 𝘥𝘰𝘯'𝘵 𝘳𝘦𝘱𝘳𝘦𝘴𝘦𝘯𝘵 𝘵𝘩𝘰𝘴𝘦 𝘰𝘧 𝘮𝘺 𝘤𝘶𝘳𝘳𝘦𝘯𝘵 𝘰𝘳 𝘱𝘢𝘴𝘵 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘳𝘴.

Low health literacy isn't a patient problem. 𝗜𝘁'𝘀 𝗮 𝘀𝘆𝘀𝘁𝗲𝗺 𝗱𝗲𝘀𝗶𝗴𝗻 𝗳𝗮𝗶𝗹𝘂𝗿𝗲. When hospitals and health systems communicate in ways patients can't understand, the cost doesn't just show up in readmission rates or patient satisfaction scores. It shows up in: – Preventable complications – Medication errors – Longer hospital stays – Staff frustration – Legal liability We're talking: • Missed discharge instructions • Incorrect medication dosing • Delayed follow-up care • Repeated ER visits • Preventable adverse events The cost? Over $𝟐𝟑𝟔 𝗯𝗶𝗹𝗹𝗶𝗼𝗻 annually in the US alone. And that's just direct medical costs. This isn't a patient education issue. It's an institutional communication failure. 🛠 So what's the fix? Start with design—communication that prioritizes clarity over convenience. Not simplified dumbing down. Not one-size-fits-all. But evidence-based, plain language, culturally responsive health communication that patients actually understand—and can act on. 📊 Research shows plain language health materials reduce hospital readmissions by up to 30% (AHRQ). That's not nice-to-have— that's patient safety infrastructure. Because when systems communicate clearly, patients heal faster. And when patients heal faster, everyone wins. 💬 DM me if you want to talk strategy. ♻️ Share this if health equity matters to your work. Cost estimate based on: • Preventable hospitalizations: $100B+ • Medication non-adherence: $100B+ • System inefficiencies: $36B+ Sources: AHRQ (2020), IOM (2004), Health Affairs (2019)

👨👩👧 Piloting a Young Adult–Led Model for Family Sodium Reduction 🍽️ What if young adults were empowered not just to cut their own sodium intake, but to influence their families’ eating habits too? 🍲👨👩👧👦 That was the goal of our pilot study, Supporting Household heAlth through familY-led Promotion (SHAYP). Because diets are shaped by shared meals, routines, and traditions, and family members know each other’s habits intimately, households are a powerful setting for driving meaningful dietary change. We developed SHAYP as a family-led digital program, co-created with young adults and grounded in the Theory of Planned Behavior and Family Systems Theory. Over six weeks, participants completed short video lessons 🎥, set SMART goals through interactive assignments 📝, received personalized WhatsApp feedback 💬, and then implemented their action plans for four weeks, whether ordering healthier dishes at hawker centers, encouraging low-sodium cooking swaps, or reshaping grocery routines. ✨ The results: Among the 114 participants (35 young adults and 79 family members), both groups showed significant improvements in sodium-related knowledge, behaviors, intentions, and confidence to make healthier choices. Many of the most impactful strategies happened outside the home, underscoring the importance of Singapore’s eating-out culture for family dietary change. ➡️ What’s next: We are preparing a larger controlled trial to rigorously test the impact of the SHAYP model. This study will compare our young adult–led family model against traditional, passive individual-focused health promotion and a family-wide model (where all members are enrolled directly). The goal is to see whether empowering just one young adult can generate the same household benefits as more intensive family-wide approaches, while requiring far fewer resources and less logistical complexity. We have additional analyses of SHAYP on the way, including a network analysis of dietary influence dynamics in SHAYP families and a photovoice study unpacking the influence pathways used by young adults. 👏 Congratulations to Kimberly Low for leading this study, and thanks to Ian Yi Han ANG, Mary Chong, and Cindy Mei Jun Chan for their invaluable contributions. Full article attached!

Effectiveness of Interactive vs. Non-Interactive Social Media Campaigns: What Works Best? Not all social media interventions are created equal. Social media effectiveness often depends on how the intervention is designed. Let's look at key differences between interactive and non-interactive social media campaigns and what the evidence says about their effectiveness. Interactive vs. Non-Interactive Social Media Campaigns Interactive Campaigns: What They Are: These enable two-way communication, encouraging active engagement. Participants interact directly with peers, facilitators, or healthcare providers through comments, discussions, or real-time chats. Examples: Facebook groups for weight management, Instagram Live Q&A sessions, or mobile apps with community forums. Key Feature: Users are co-creators of the experience, building a sense of community and accountability. Non-Interactive Campaigns: What They Are: These rely on one-way communication, delivering information without enabling user interaction. Examples: Educational videos on YouTube, infographics posted on Instagram, or pre-scheduled tweets. Key Feature: Focus is on disseminating knowledge to a broad audience without engaging users directly. Which is More Effective? According to a Cochrane Review on social media interventions for health behavior change: Effectiveness of Interactive Campaigns: Found to be more effective in areas like: Physical Activity: A meta-analysis of 29 studies showed a small but significant positive effect on increasing physical activity (SMD: 0.29; 95% CI: 0.13–0.45). Weight Loss: Interactive interventions led to notable reductions in weight and BMI (MD: -1.33 kg; 95% CI: -2.00 to -0.67). Well-Being: Enhanced quality of life and global well-being were reported (SMD: 0.46; 95% CI: 0.14–0.79). Why It Works: Interactive campaigns leverage social support, accountability, and personalized feedback, which are crucial for sustaining behavior change. Effectiveness of Non-Interactive Campaigns: Primarily effective for awareness and education, such as improving knowledge about health conditions. Limitations: Without active engagement, these campaigns showed minimal impact on behavior change metrics like physical activity or diet quality. Illustrating the Difference Imagine a campaign to promote physical activity: Interactive: A community fitness challenge on Facebook where users share daily progress, receive feedback from trainers, and motivate each other in real time. Non-Interactive: A series of scheduled posts on Instagram providing tips for staying active, without opportunities for user engagement or feedback. Conclusion: Engagement is Key Interactive campaigns are better suited for driving meaningful behavior change. By fostering community, accountability, and real-time feedback, they address the psychological and social factors critical for sustained improvement. #SocialMedia #PublicHealth #BehaviorChange #HealthPromotion #DigitalEngagement

The Role of Behavioral Science in Health Promotion: Strategies for Effective Interventions 1. Understand Human Behavior Recognize that health behaviors are influenced by many factors like environment, social norms, and individual beliefs. Tailor interventions to address these factors. 2. Use Positive Reinforcement Encourage healthy behaviors by rewarding them. This could be through praise, incentives, or recognition. 3. Leverage Social Proof People are more likely to adopt a behavior if they see others doing it. Highlight stories of individuals or groups who have successfully adopted healthy habits. 4. Simplify Choices Make the healthy choice the easy choice. Reduce barriers that make it hard for people to adopt healthy behaviors. 5. Provide Clear, Actionable Information Give people straightforward steps they can take to improve their health. Avoid jargon and complex instructions. 6. Create Supportive Environments Ensure that the environment supports healthy behaviors. This could mean providing access to healthy foods or creating spaces for physical activity. 7. Use Technology Wisely Leverage apps, reminders, and online communities to support health behaviors. Technology can provide constant support and reminders to stay on track. Implement these strategies to promote health effectively. Help people make better choices and lead healthier lives.