1c EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE THE CHALLENGE Addressing the burden of chronic disease begins at home. Many of the leading causes of ill health in member countries in the Organisation for Economic Co- operation and Development (OECD) are caused, at least in part, by modifiable risk factors— diet, physical inactivity, tobacco use, and alcohol consumption, among others—that become embedded in families’ daily routines, making change difficult even when they want to adopt healthier behaviors. Once chronic disease or an acute episode strikes, effective management likewise requires patients to be active partners in designing and managing their own care. New solutions are needed to make it easier for families and individuals to sustain long-term care for chronic conditions; to help them become active partners in their medical care; and to empower them to adopt and maintain new behaviors for longer and healthier lives. PEOPLE WANT TO MAKE HEALTHIER LIFESTYLE CHOICES, BUT STRUGGLE TO SUSTAIN HEALTHY BEHAVIORS Increasingly, the burden of disease in OECD countries is driven by behavioral and lifestyle risk factors, leading to long-term morbidity, preventable death, and skyrocketing health expenditure. Obesity prevalence, for example, ranges between 15% and 38% in many OECD countries, and is rising in most.i Likewise, tobacco use is responsible for 12% of all deaths globallyii and expenditure on smoking-attributable diseases climbed to $467 billion in 2012.iii Individuals generally say they want to adopt healthier behaviors, but the lack discipline and follow-up they need to sustain behavior change in the long run. For example, more than two- thirds of U.S. smokers report wanting to quit, and more than half tried to quit in the past year—but only a tiny portion succeed,iv and even those who reach the one-year abstinence mark continue to face a 10% annual risk of relapse.v Similarly, about half of overweight or obese people in the U.S. report they tried to lose weight within the past year— though the proportion attempting to do so has fallen since 1990.vi Japan Trust Fund for OCTOBER 2018 Scaling Up Nutrition EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE Low Cost and Convenience Push Families Toward Suboptimal Nutrition The hazards of poor diets are well established, but eating healthy can be a challenge for many Consumption of families. One meta-analysis suggests that healthier diets cost about $1.50 more per day per ready-made meals person than less healthy options;vii the difference may seem small in a wealthy country has been setting, but over the course of a year it would translate to about 10% of the total household associated with income for a family of four living at the U.S. federal poverty line.viii Convenience is also a major higher calorie factor. Consumption of ready-made meals has been associated with higher calorie consumption and abdominal obesity,ix and evidence suggests that children may avoid fruits consumption and and vegetables in part because the children did not think of them as convenient snack foods.x abdominal obesity, Despite popular attention, there is little evidence that the geographic availability of food (e.g., and evidence food deserts and fast food density) meaningfully impact food consumption patterns.xi suggests that children may avoid Patients Are Not Set Up for Success in Managing Their Own fruits and Chronic Disease vegetables in part Particularly for long-term chronic diseases, patient adherence to care is necessary to because the coproduce positive health outcomes—but the health system does not always engage patients and facilitate their co-production, leading to problems with adherence and follow-up. A 2003 children did not World Health Organization report estimated that average global adherence to long-term think of them as therapies is just 50%.xii More recent large-scale study findings from the U.S. appear to validate convenient snack that general range: 73% of American patients with hypertension, but just 37% with gout, foods. achieved at least 80% adherence to prescribed therapy.xiii In qualitative studies, chronic disease patients say mistrust, confusion, and alienation from the treatment planning process are barriers to treatment adherence.xiv THE PATH FORWARD: BETTER HEALTH IN THE HOME Self-Help: New Self-Led Tools to Support Healthier Behaviors In recent years, mobile apps to support healthy behavior have exploded in number and popularity. Systematic reviews and individual studies offer almost universal support for mobile apps—under controlled conditions—as a tool to help people eat more fruits and vegetables;xv lose weight;xvi be more physically active;xvii better manage their diabetes;xviii increase their success in quitting smoking;xix and manage depression and anxiety at lower cost.xx App prices are also extremely low relative to most wealthy country health interventions, suggesting that even marginal gains in health benefits would be extraordinary cost-effective. Yet despite this promise, identifying and scaling the most effective apps faces informational and regulatory challenges. Apps are not a static intervention; they are created through an iterative development process that is difficult to evaluate under the existing paradigms of randomized clinical trials.xxi An alternative approach can both evaluate the principles a mobile app should follow, and then rate the app’s compliance with evidence-based practices.xxii Even where solid evidence exists, however, consumers can struggle to identify good evidence- based options in the unregulated app marketplace, where apps can vary in widely in their use OCTOBER 2018 2 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE of evidence-based practices and may even contain actively harmful content.xxiii Payers, governments, and providers can potentially play act as gatekeepers to quality-assured health apps; see more on regulation and accreditation for this emerging space in Brief 15c. Other approaches to self-led behavior change have also gained popularity, but are not Voluntary necessarily supported by strong evidence. Structured activity and wellness programs offer a commitment promising but under-evaluated path to change sedentary lifestyle patterns; for example, the devices use National Health Service in the U.K. officially endorses a “Couch to 5K” program (supported by behavioral multiple mobile apps) designed to gradually increase physical activity levels, but the initiative has not been rigorously studied.xxiv Personal activity trackers increasingly adorn the wrists of economic theory— young and old alike; systematic review evidence suggests they may be marginally useful in particularly the promoting weight loss among adults and the elderly, but not young peoplexxv—and one study principle of loss suggests young people lose their motivation to exercise when wearing the devices.xxvi Finally, aversion as a voluntary commitment devices use behavioral economic theory—particularly the principle of contracts loss aversion as a contracts motivator—to encourage self-discipline (see the Spotlight section motivator—to for an example). Through these mechanisms, individuals put aside their own resources with encourage self- the understanding that they can only get those assets back after they meet their own pre- determined goals. Variations on voluntary commitment contracts appear to have helped discipline. support smoking cessation in the Philippinesxxvii and Thailand.xxviii In the U.S., one study found that the contracts helped increase weight loss in an obese population—but the effect quickly eroded after the end of the contract period.xxix Top Interventions Intervention Evidence Strength Research Findings Mobile applications for behavior change Strong Positive Structured activity and wellness programs None N/A Personal activity trackers Moderate Mixed Voluntary commitment contracts Moderate Positive/Mixed Mobile produce markets Low Positive Healthier products in vending machines Moderate Positive When families Healthy meal delivery kits None N/A want to adopt Subsidies for fruits and vegetables Moderate Positive healthier diets, a Personalized care planning Strong Positive range of mHealth for treatment adherence Strong Positive interventions and 90-day prescriptions/automatic refill Moderate Positive innovations that change the cost or Changing the Calculus for Healthy Eating convenience of When families want to adopt healthier diets, a range of interventions and innovations that change the cost or convenience of nutritious meals can help them make healthy eating a nutritious meals reality. Mobile produce markets—essentially farmers’ markets on wheels—have been can help them associated with increased consumption of fruits and vegetables in a systematic review, make healthy though most of the underlying evidence is of poor quality.xxx Likewise, introducing healthier eating a reality. options in vending machines—sometimes paired with lowering prices—appears to increase the consumption of the healthier foods, but the effect on nutritional outcomes is still poorly evaluated.xxxi Private sector investment is now supercharging access to healthy snacks through franchised healthy vending machine networks like Healthy Fresh Vending and Vend Natural. Further expanding the range of convenient available offerings, Farmers Fridge sells OCTOBER 2018 3 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE healthy fresh-made salads, bowls, sandwiches, wraps, snacks, and beverages through 100- plus sophisticated vending machines across greater Chicago and Milwaukee in the United States.xxxii However, these programs—and other private sector efforts to improve food convenience like meal delivery kits for home cooking—have not yet been rigorously evaluated vis-à-vis nutritional outcomes. Other efforts seek to make healthy eating more affordable—and thus more desirable for families struggling to make ends meet. A 2013 systematic review found limited available evidence, but identified a consistent relationship between subsidies for healthier foods and their increased consumption.xxxiii In the interim, evidence for healthy food subsidies has A 2013 systematic continued to grow. In Australia, a program providing boxes of highly subsidized fruits and review found vegetables to disadvantaged people led to improved nutritional biomarkers after 12 months, limited available despite unchanged self-reported consumption of fruits and vegetables.xxxiv In the United evidence, but States, the Healthy Incentives Pilot, for example, offered 30% rebates on purchases of fruits and vegetables using federal nutrition assistance and consumption subsequently rose by .24 identified a servings per day.xxxv However, evidence suggests that fruit and vegetable consumption consistent typically reverts to baseline levels after the incentives end, suggesting long-term subsidies are relationship needed to sustain dietary change.xxxvi between subsidies for healthier foods Patients as Partners: New Approaches to Engaging Individuals in and their increased Their Own Care Needs consumption. Most care for chronic conditions and rehabilitation happens at home, where patients must take charge of their own care plans to produce positive health outcomes. Personalized care planning—where patients partner with their health provider to craft appropriate and feasible plans for managing their own care—has been associated with small but significant health improvements for some chronic conditions in a systematic review, plus gains in patients’ belief in their self-efficacy to manage their health.xxxvii In addition, strong evidence suggests that mhealth interventions, including mobile applicationsxxxviii and text message reminders,xxxix can substantially increase medication adherence by patients with chronic conditions. But the potential scope for mhealth to engage patients as partners is even more expansive. A study from Australia, for example, finds that an app-supported rehabilitation home exercise program produced better adherence than paper-based instructions alone;xl and a feasibility study suggests that patients can help monitor post-operative wound healing by taking and transmitting images of the wound site.xli An alternative approach seeks to make adherence to care easier for patients, removing some of the barriers that may be causing them to stop following their treatment protocols. Increasingly, strong evidence from large-scale trials supports the use of automatic prescription refills,xlii late-to-refill reminder calls,xliii and the use of 90-day prescriptions to increase adherence to chronic disease medication regimens.xliv OCTOBER 2018 4 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE SPOTLIGHT SticKKing to Goals for Better Health ► Each January, up to 83% of people in the United States make a New Year’s Resolution, often promising to lose weight, change their lifestyle, or quit smoking. But months later, only 9.2% of resolution-makers feel they consistently succeed in achieving their resolution goals.xlv This disconnect—between people’s goals and their ability to realize them—is one of the thorniest barriers to adopting healthier behaviors. Drawing from their own research around the world, in 2007 a behavioral economics research team at Yale University launched StickK.com, a novel online tool to help people “stick” to their own goals. Through StickK, users first define their personalized goal; in practice, many (but far from all) goals are health or lifestyle-related. Users can then create an optional monetary “commitment contract,” offering their own funds for a deposit; they can also appoint a “referee” to monitor their progress and increase their accountability. If they hit their goal, they get their money back; if they fall short, the money goes to a third-party recipient of their choosing.xlvi The most powerful commitment contracts designate an “anti-charity”—an organization with diametrically opposed values and goals to the commitment-maker—as the recipient of funds in the case of failure.xlvii By 2018, StickK reported that its users had created 415,000 commitment contracts, putting a total of $37 million on the line.xlviii Though its design draws from research evidence, StickK has not been rigorously evaluated; usage statistics suggest that 85% of users with monetary contracts achieved their reported goals, compared to 46% among users with nonmonetary stakes.xlix However, these figures must be treated with some caution; because results are typically self-reported, users with monetary stakes have a stronger incentive to misreport their own progress. ENDNOTES i OECD, “Obesity Update 2017” (OECD, 2017), https://www.oecd.org/els/health-systems/Obesity- Update-2017.pdf. ii World Health Organization, “WHO Global Report: Mortality Attributable to Tobacco” (Gevena: World Health Organization, 2012), http://apps.who.int/iris/bitstream/handle/10665/44815/9789241564434_eng.pdf;jsessionid=384 D02C141BDCDDE6F17435C791DD90E?sequence=1. iii Mark Goodchild, Nigar Nargis, and Edouard Tursan d’Espaignet, “Global Economic Cost of Smoking-Attributable Diseases,” Tobacco Control 27, no. 1 (January 1, 2018): 58–64, https://doi.org/10.1136/tobaccocontrol-2016-053305. iv Centers for Disease Control, “Smoking and Tobacco Use; Fact Sheet; Smoking Cessation,” Centers for Disease Control and Prevention - Smoking and Tobacco Use, 2017. Accessed September 23, 2018. http://www.cdc.gov/tobacco/data_statistics/fact_sheets/quitting/. v John R. Hughes, Erica N. Peters, and Shelly Naud, “Relapse to Smoking After 1 Year of Abstinence: A Meta-Analysis,” Addictive Behaviors 33, no. 12 (December 2008): 1516–20, https://doi.org/10.1016/j.addbeh.2008.05.012. vi Kassandra R. Snook et al., “Change in Percentages of Adults With Overweight or Obesity Trying to Lose Weight, 1988-2014,” JAMA 317, no. 9 (March 7, 2017): 971–73, https://doi.org/10.1001/jama.2016.20036. OCTOBER 2018 5 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE vii Mayuree Rao et al., “Do Healthier Foods and Diet Patterns Cost More than Less Healthy Options? A Systematic Review and Meta-Analysis,” BMJ Open 3, no. 12 (December 4, 2013), https://doi.org/10.1136/bmjopen-2013-004277. viii U.S Centers for Medicare & Medicaid Services, “Federal Poverty Level (FPL),” HealthCare.gov, accessed September 23, 2018, https://www.healthcare.gov/glossary/federal-poverty-level-fpl/. ix Ala’a Alkerwi, Georgina E. Crichton, and James R. Hébert, “Consumption of Ready-Made Meals and Increased Risk of Obesity: Findings from the Observation of Cardiovascular Risk Factors in Luxembourg (ORISCAV-LUX) Study,” The British Journal of Nutrition 113, no. 2 (January 28, 2015): 270–77, https://doi.org/10.1017/S0007114514003468. x Rikke Krølner et al., “Determinants of Fruit and Vegetable Consumption among Children and Adolescents: A Review of the Literature. Part II: Qualitative Studies,” The International Journal of Behavioral Nutrition and Physical Activity 8 (October 14, 2011): 112, https://doi.org/10.1186/1479- 5868-8-112. xi Laura K. Cobb et al., “The Relationship of the Local Food Environment with Obesity: A Systematic Review of Methods, Study Quality, and Results,” Obesity 23, no. 7 (July 1, 2015): 1331–44, https://doi.org/10.1002/oby.21118. xii Eduardo Sabaté, Adherence to Long-Term Therapies: Evidence for Action (Geneva: World Health Organization, 2003), http://apps.who.int/medicinedocs/en/d/Js4883e/. xiii Becky A. Briesacher et al., “Comparison of Drug Adherence Rates Among Patients with Seven Different Medical Conditions,” Pharmacotherapy 28, no. 4 (April 2008): 437–43, https://doi.org/10.1592/phco.28.4.437. xiv Neus Pagès-Puigdemont et al., “Patients’ Perspective of Medication Adherence in Chronic Conditions: A Qualitative Study,” Advances in Therapy 33, no. 10 (2016): 1740–54, https://doi.org/10.1007/s12325-016-0394-6; Shiraz I. Mishra et al., “Adherence to Medication Regimens among Low-Income Patients with Multiple Comorbid Chronic Conditions,” Health & Social Work 36, no. 4 (November 2011): 249–58, https://www.ncbi.nlm.nih.gov/pubmed/22308877. xv Sarah Mummah et al., “Effect of a Mobile App Intervention on Vegetable Consumption in Overweight Adults: A Randomized Controlled Trial,” The International Journal of Behavioral Nutrition and Physical Activity 14 (September 15, 2017), https://doi.org/10.1186/s12966-017- 0563-2; Sarah Pietertje Elbert, Arie Dijkstra, and Anke Oenema, “A Mobile Phone App Intervention Targeting Fruit and Vegetable Consumption: The Efficacy of Textual and Auditory Tailored Health Information Tested in a Randomized Controlled Trial,” Journal of Medical Internet Research 18, no. 6 (June 10, 2016), https://doi.org/10.2196/jmir.5056. xvi Lynnette Nathalie Lyzwinski, “A Systematic Review and Meta-Analysis of Mobile Devices and Weight Loss with an Intervention Content Analysis,” Journal of Personalized Medicine 4, no. 3 (June 30, 2014): 311–85, https://doi.org/10.3390/jpm4030311; Gemma Flores Mateo et al., “Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis,” Journal of Medical Internet Research 17, no. 11 (November 10, 2015): e253, https://doi.org/10.2196/jmir.4836. xvii Jason Fanning, Sean P Mullen, and Edward McAuley, “Increasing Physical Activity With Mobile Devices: A Meta-Analysis,” Journal of Medical Internet Research 14, no. 6 (November 21, 2012), https://doi.org/10.2196/jmir.2171. xviii X. Liang et al., “Effect of Mobile Phone Intervention for Diabetes on Glycaemic Control: A Meta- Analysis,” Diabetic Medicine 28, no. 4 (April 1, 2011): 455–63, https://doi.org/10.1111/j.1464- 5491.2010.03180.x. xix Robyn Whittaker et al., “Mobile Phone-Based Interventions for Smoking Cessations,” Cochrane Database of Systematic Reviews 4, no. CD006611 (2016), https://doi.org/10.1002/14651858.CD006611.pub4. xx Joseph Firth et al., “The Efficacy of Smartphone‐based Mental Health Interventions for Depressive Symptoms: A Meta‐analysis of Randomized Controlled Trials,” World Psychiatry 16, no. 3 (October 2017): 287–98, https://doi.org/10.1002/wps.20472; Joseph Firth et al., “Can Smartphone Mental Health Interventions Reduce Symptoms of Anxiety? A Meta-Analysis of Randomized Controlled Trials,” Journal of Affective Disorders 218 (15 2017): 15–22, https://www.sciencedirect.com/science/article/pii/S0165032717300150.; Kien Hoa Ly et al., “Smartphone-Supported versus Full Behavioural Activation for Depression: A Randomised Controlled Trial,” PLoS ONE 10, no. 5 (May 26, 2015), https://doi.org/10.1371/journal.pone.0126559. OCTOBER 2018 6 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE xxi David Peiris, J. Jaime Miranda, and David C. Mohr, “Going beyond Killer Apps: Building a Better mHealth Evidence Base,” BMJ Global Health 3, no. 1 (February 21, 2018), https://doi.org/10.1136/bmjgh-2017-000676. xxii David C. Mohr et al., “Trials of Intervention Principles: Evaluation Methods for Evolving Behavioral Intervention Technologies,” Journal of Medical Internet Research 17, no. 7 (July 8, 2015): e166, https://doi.org/10.2196/jmir.4391. xxiii Mark Erik Larsen, Jennifer Nicholas, and Helen Christensen, “A Systematic Assessment of Smartphone Tools for Suicide Prevention,” PLOS ONE 11, no. 4 (April 13, 2016): e0152285, https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152285. xxiv NHS, “Couch to 5K: Week by Week,” nhs.uk, April 30, 2018, https://www.nhs.uk/live- well/exercise/couch-to-5k-week-by-week/. xxv Scott W. Cheatham et al., “The Efficacy of Wearable Activity Tracking Technology as Part of a Weight Loss Program: A Systematic Review,” The Journal of Sports Medicine and Physical Fitness 58, no. 4 (April 2018): 534–48, https://doi.org/10.23736/S0022-4707.17.07437-0. xxvi Charlotte Kerner and Victoria A. Goodyear, “The Motivational Impact of Wearable Healthy Lifestyle Technologies: A Self-Determination Perspective on Fitbits With Adolescents,” American Journal of Health Education 48, no. 5 (September 3, 2017): 287–97, https://doi.org/10.1080/19325037.2017.1343161. xxvii Xavier Giné, Dean Karlan, and Jonathan Zinman, “Put Your Money Where Your Butt Is: A Commitment Contract for Smoking Cessation” (The World Bank, July 2009), https://openknowledge.worldbank.org/bitstream/handle/10986/4177/WPS4985.pdf?sequence=1&isAll owed=y. xxviii Justin S. White, William H. Dow, and Suthat Rungruanghiranya, “Commitment Contracts and Team Incentives,” American Journal of Preventive Medicine 45, no. 5 (November 2013), https://doi.org/10.1016/j.amepre.2013.06.020. xxix Leslie K. John et al., “Financial Incentives for Extended Weight Loss: A Randomized, Controlled Trial,” Journal of General Internal Medicine 26, no. 6 (June 1, 2011): 621–26, https://doi.org/10.1007/s11606-010-1628-y. xxx Bi-Sek Hsiao, Lindiwe Sibeko, and Lisa M. Troy, “A Systematic Review of Mobile Produce Markets: Facilitators and Barriers to Use, and Associations with Reported Fruit and Vegetable Intake,” Journal of the Academy of Nutrition and Dietetics, May 12, 2018, https://doi.org/10.1016/j.jand.2018.02.022. xxxi A. Grech and M. Allman‐Farinelli, “A Systematic Literature Review of Nutrition Interventions in Vending Machines That Encourage Consumers to Make Healthier Choices,” Obesity Reviews 16, no. 12 (December 1, 2015): 1030–41, https://doi.org/10.1111/obr.12311. xxxii Farmer’s Fridge, “Locate a Farmer’s Fridge,” Farmer’s Fridge, accessed September 23, 2018, https://www.farmersfridge.com/locations. xxxiii Ruopeng An, “Effectiveness of Subsidies in Promoting Healthy Food Purchases and Consumption: A Review of Field Experiments,” Public Health Nutrition 16, no. 7 (July 2013): 1215–28, https://doi.org/10.1017/S1368980012004715. xxxiv Andrew P. Black et al., “Nutritional Impacts of a Fruit and Vegetable Subsidy Programme for Disadvantaged Australian Aboriginal Children,” British Journal of Nutrition 110, no. 12 (December 2013): 2309–17, https://doi.org/10.1017/S0007114513001700. xxxv Susan Bartlett et al., “Evaluation of the Health Incentives Pilot (HIP): Final Report” (U.S. Department of Agriculture, September 2014), https://fns- prod.azureedge.net/sites/default/files/ops/HIP-Final.pdf. xxxvi Marie Steele-Adjognon and Dave Weatherspoon, “Double Up Food Bucks Program Effects on SNAP Recipients’ Fruit and Vegetable Purchases,” BMC Public Health 17 (December 12, 2017), https://doi.org/10.1186/s12889-017-4942-z; Etienne J. Phipps et al., “Impact of a Rewards-Based Incentive Program on Promoting Fruit and Vegetable Purchases,” American Journal of Public Health 105, no. 1 (January 2015): 166–72, https://www.ncbi.nlm.nih.gov/pubmed/24625144. xxxvii A. Coulter et al., “Personalized Care Planning for Adults with Chronic or Long-Term Health Conditions,” Cochrane Database of Systematic Reviews 3, no. CD010523 (2015), https://doi.org/10.1002/14651858.CD010523.pub2. xxxviii Yousuf Gandapur et al., “The Role of MHealth for Improving Medication Adherence in Patients with Cardiovascular Disease: A Systematic Review,” European Heart Journal - Quality of Care and Clinical Outcomes 2, no. 4 (October 1, 2016): 237–44, https://doi.org/10.1093/ehjqcco/qcw018. OCTOBER 2018 7 EMPOWERING HOUSEHOLDS AND INDIVIDUALS TO CO-PRODUCE POSITIVE HEALTH OUTCOMES… FOR DIGNIFIED, PERSON-CENTERED CARE AMIDST DEMOGRAPHIC CHANGE xxxix Jay Thakkar et al., “Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-Analysis,” JAMA Internal Medicine 176, no. 3 (March 2016): 340–49, https://doi.org/10.1001/jamainternmed.2015.7667. xl Tara E Lambert et al., “An App with Remote Support Achieves Better Adherence to Home Exercise Programs than Paper Handouts in People with Musculoskeletal Conditions: A Randomised Trial,” Journal of Physiotherapy 63, no. 3 (July 1, 2017): 161–67, https://doi.org/10.1016/j.jphys.2017.05.015. xli Rebecca L. Gunter et al., “Feasibility of an Image-Based Mobile Health Protocol for Postoperative Wound Monitoring,” Journal of the American College of Surgeons 226, no. 3 (March 1, 2018): 277– 86, https://doi.org/10.1016/j.jamcollsurg.2017.12.013. xlii Corey A. Lester, David A. Mott, and Michelle A. Chui, “The Influence of a Community Pharmacy Automatic Prescription Refill Program on Medicare Part D Adherence Metrics,” Journal of Managed Care & Specialty Pharmacy 22, no. 7 (June 27, 2016): 801–7, https://doi.org/10.18553/jmcp.2016.22.7.801; Olga S. Matlin et al., “Community Pharmacy Automatic Refill Program Improves Adherence to Maintenance Therapy and Reduces Wasted Medication,” The American Journal of Managed Care 21, no. 11 (November 2015): 785–91. xliii Michael S Taitel et al., “Impact of Late-to-Refill Reminder Calls on Medication Adherence in the Medicare Part D Population: Evaluation of a Randomized Controlled Study,” Patient Preference and Adherence 11 (February 28, 2017), https://doi.org/10.2147/PPA.S127997. xliv R. S. Leslie, T. Gilmer, L. Natarajan, and M. 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