ArticlePDF Available

Automated Hovering in Health Care - Watching Over the 5000 Hours



The dominant form of health care financing in the United States supports a reactive, visit-based model in which patients are seen when they become ill, typically during hospitalizations and at outpatient visits. That care model falls short not just because it is expensive and often fails to proactively improve health, but also because so much of health is explained by individual behaviors,(1) most of which occur outside health care encounters. Indeed, even patients with chronic illness might spend only a few hours a year with a doctor or nurse, but they spend 5000 waking hours each year engaged in everything . . .
july 5, 2012
n engl j med 367;1 july 5, 2012 1
outpatient visits. That care model
falls short not just because it is
expensive and often fails to pro-
actively improve health, but also
because so much of health is ex-
plained by individual behaviors,
most of which occur outside
health care encounters. Indeed,
even patients with chronic illness
might spend only a few hours a
year with a doctor or nurse, but
they spend 5000 waking hours
each year engaged in everything
else — including deciding wheth-
er to take prescribed medications
or follow other medical advice, de-
ciding what to eat and drink and
whether to smoke, and making
other choices about activities that
can profoundly affect their health.
The increasing attention being
paid to those 5000 hours takes
various forms. Employers are fo-
cusing more on employees’ well-
ness — how they eat, whether
they smoke, and how much they
exercise. Medication adherence has
become a more important goal,
thanks to growing recognition
that many people with chronic
conditions fail to take their medi-
cations regularly and therefore do
not get the benefits that health
care can provide. Home-based bio-
metric assessments of indicators
such as glucose level, blood pres-
sure, and weight are emerging as
part of longitudinal clinical care.
Transitional care models are be-
ing touted as a way of coordinat-
ing care beyond hospitalization.
And hospitals and health plans
are developing “hot-spotter” ap-
proaches, deploying tailored and
intensive attention to managing
the care of their most challeng-
ing patients.
All these activities
occur outside the conventional,
billable, clinical encounter — and
all reflect some sort of hovering
over people in their daily lives.
Conventional approaches to im-
proving patient engagement along
these dimensions have been per-
sonnel-intensive — using visiting
nurses or clinically staffed tele-
medicine services. Although re-
sults have been mixed, in general
these programs have not fulfilled
their promise. One problem is
that using personnel in hovering
is expensive and therefore diffi-
cult to scale up and to justify, ex-
cept for the very sickest patients,
some of whom might be too sick
to benefit. Another problem is
Automated Hovering in Health Care — Watching
Over the 5000 Hours
David A. Asch, M.D., M.B.A., Ralph W. Muller, M.A., and Kevin G. Volpp, M.D., Ph.D.
The dominant form of health care financing in
the United States supports a reactive, visit-
based model in which patients are seen when they
become ill, typically during hospitalizations and at
The New England Journal of Medicine
Downloaded from on November 4, 2015. For personal use only. No other uses without permission.
Copyright © 2012 Massachusetts Medical Society. All rights reserved.
n engl j med 367;1 july 5, 2012
that initiating and maintaining
patient engagement is difficult.
A large multicenter trial of tele-
monitoring for patients with heart
failure showed no effect on the
primary outcomes of rehospital-
ization and death; moreover, 14%
of those assigned to the interven-
tion group would not use the
system at all, and nearly half of
those who did lost interest over
time. One challenge, therefore, is
finding a way to automate hover-
ing to reduce its cost. A related
challenge is figuring out how to
incorporate it into people’s lives
in ways that are not just accept-
able and convenient, but ideally
even welcomed.
Three recent developments sug-
gest that automated hovering may
offer promise. First are early ef-
forts at payment mechanisms that
support more accountability for
health outcomes including
nonreimbursement for prevent-
able readmissions and bundling of
payments around the goals of care
rather than encounters. These
changes provide a financial en-
gine to support automated hover-
ing initiatives.
The second development is
our deepening understanding of
behavioral economics and the re-
ality that although most people
want better health and typically
know what it would take to
achieve it, the desires, distractions,
and urgencies of the moment of-
ten get in the way of pursuing
what’s in their own long-term
self-interest. Behavioral econom-
ics explains why people are pre-
dictably irrational and provides
tools for redirecting their behav-
ior with carefully deployed nudg-
es and financial incentives.
The third development is the
expanded reach of both sophisti-
cated and simple technologies —
cell phones, wireless devices, and
the Internet — that can help
health experts connect to people
during their everyday lives. Nei-
ther wireless devices nor behav-
ioral economics were part of the
disease-management programs
that have produced mixed results
in the past.
There is already considerable
evidence of the promise of auto-
mated hovering. One study of pa-
tients taking warfarin deployed a
home-based pill dispenser that
was electronically tethered to a
lottery system. Patients were au-
tomatically entered into a daily
random drawing, with a small
chance of winning $100 and a
larger chance of winning $10.
Each day, patients were electroni-
cally notified if their number had
come up which it would do
about 1 day in 5 — but were eli-
gible for the prize only if they
had taken their warfarin the pre-
vious day, as signaled by the dis-
penser. The system provided daily
engagement, the chance of a prize,
and a sense of anticipated regret:
no one wants to receive news of
winning only to be disqualified
for nonadherence the previous day.
The expected value of the lottery
was less than $3 per day, but the
system reduced the rate of incor-
rect doses from 22% to about 3%
and reduced the rate of out-of-
range international normalized
ratios from 35% to 12%.
Such a
system could easily be deployed
to improve medication adherence
among patients discharged from
the hospital with congestive heart
failure or after being treated for
acute coronary syndromes. This
system uses technology with an
engagement strategy informed by
behavioral economics to hover
over patients.
In another clinical trial, pa-
tients with difficult-to-control di-
abetes were randomly assigned to
receive usual care or mentorship
from another patient who had
previously managed to tame his
or her own diabetes. The mentor
merely had to call the patient once
a week. The result at 6 months was
glycated hemoglobin levels more
than a full percentage point lower
than those in the control group,
created by a system requiring
minimal technology to produce
hovering that was “automatic”
from the clinician’s perspective.
This kind of hovering must be
targeted to the right clinical and
social circumstances. The biggest
savings will probably come from
reducing preventable hospitaliza-
tions or delaying entrance into
nursing homes, because that’s
where so much spending current-
ly occurs. However, cell-phone
mentors and automatic pill-bot-
tle reminders probably won’t of-
fer much to patients who are fre-
quently hospitalized owing to a
combination of severe illness and
challenging life circumstances.
These patients, at one end of the
spectrum of intensity of health
care needs, require a more per-
sonnel-intensive approach that fo-
cuses as much on social circum-
stances as on complex medical
care. The best targets for auto-
mated hovering are conditions
whose management depends sub-
stantially on individual patients’
behavior. Good targets are medi-
cation adherence in patients with
heart failure or acute coronary
syndromes and efforts to manage
diet, exercise, or weight. The
amount of hovering required to
engage patients in healthy behav-
iors during those 5000 hours will
depend critically on the intensity
of their needs, but automated
systems might be a cost-effective
solution for many patients.
There are potential concerns.
Some people might worry that
Auto mated Hover ing in He alth C are
The New England Journal of Medicine
Downloaded from on November 4, 2015. For personal use only. No other uses without permission.
Copyright © 2012 Massachusetts Medical Society. All rights reserved.
n engl j med 367;1 july 5, 2012
too much hovering will erode pa-
tients’ sense of personal respon-
sibility or that hovering in one
area might distract providers or
patients from other important
health issues. Others may worry
that hovering is too intrusive or
paternalistic though patients
could easily opt out, and it’s ar-
guably no more paternalistic than
traditional approaches to improv-
ing patient outcomes. It will be
important to ensure that new
hovering efforts are evaluated
carefully, with assessment of both
intended and potential unintend-
ed consequences.
And of course, there is a con-
siderable amount we don’t know
about these approaches: the kinds
of patients, conditions, or set-
tings for which they will be the
most useful; the organizations
(hospitals, employers, or insur-
ers) that should be the ones to
deploy them; and how to make
them heard over the din of every-
thing else that competes for atten-
tion while remaining unintrusive
enough that nudges don’t become
self-defeating nags. There are both
clinical and research opportunities
in pursuing an approach that is
just as rigorous as our approach
to other areas of medicine. Care-
ful iterative testing is essential
because these new forms of pa-
tient engagement, whatever shape
they take, will be central to im-
proving population health in our
future health care system.
Disclosure forms provided by the authors
are available with the full text of this article
From the Center for Health Equity Research
and Promotion, Philadelphia Veterans Af-
fairs Medical Center (D.A.A., K.G.V.), the
University of Pennsylvania Health System
Center for Innovations in Health Care Fi-
nancing (D.A.A., R.W.M., K.G.V.), the Penn
CMU Roybal P30 Center in Behavioral Eco-
nomics and Health (D. A.A., K.G.V.), the
Leonard Davis Institute of Health Econom-
ics, Center for Health Incentives and Behav-
ioral Economics (D.A.A., R.W.M., K.G.V.),
and the Perelman School and Wharton
School (D.A.A., K.G.V.), University of Penn-
sylvania — all in Philadelphia.
This article was published on June 20, 2012,
1. McGinnis JM, Williams-Russo P, Knick-
man JR. The case for more active policy at-
tention to health promotion. Health Aff
(Millwood) 2002;21:78-93.
2. Gawande A. The hot spotters. The New
Yorker. January 24, 2011.
3. Volpp KG, Asch DA, Galvin R, Loewen-
stein G. Redesigning employee health incen-
tives — lessons from behavioral economics.
N Engl J Med 2011;365:388-90.
4. Volpp KG, Loewenstein G, Troxel A, et al.
A test of financial incentives to improve war-
farin adherence. BMC Health Serv Res 2008;
5. Long JA , Jahnle EC, Richardson DM,
Loewenstein G, Volpp KG. Peer mentoring
and financial incentives to improve glucose
control in African American veterans: a ran-
domized trial. Ann Intern Med 2012;156:416-
DOI: 10.1056/NEJMp1203869
Copyright © 2012 Massachusetts Medical Society.
Auto mated Hover ing in He alth C are
hree decades of research fo-
cused predominantly on
costs and the use of services
among Medicare beneficiaries
has repeatedly found wide re-
gional variations in health care
experiences and health system
Much less atten-
tion has been paid to variations
in access to care and their asso-
ciated implications for quality of
care and health outcomes. Our re-
cent Commonwealth Fund report,
“Rising to the Challenge: Results
from a Scorecard on Local Health
System Performance,
shows that
when we look beyond state aver-
ages, there are staggeringly wide
gaps in people’s ability to gain ac-
cess to care in different commu-
nities around the country. We
also find a strong and persistent
association between access and
health care quality, including the
receipt of preventive care.
Simply put, where a person
lives matters — it influences the
ability to obtain health care, as
well as the probable quality of
care that will be received —
though it should not matter in an
equitable health care system. This
and other Scorecard findings have
important implications that are
relevant to national policy reforms
and to newly available resources
for improving access and quality
of care.
The Scorecard tracks 43 health
system performance measures
grouped into four dimensions:
access, prevention and treatment,
potentially avoidable hospital use
and cost, and healthy lives. The
analysis examined the range of
variation across all 306 hospital
referral regions (HRRs) — region-
al health care markets defined
with the use of patient-flow data
for the Dartmouth Atlas of Health
Care and drew largely from
publicly available data, generally
from 2008 to 2010. (See the Sup-
plementary Appendix, available
Geographic Variation in Access to Care — The Relationship
with Quality
David C. Radley, Ph.D., M.P.H., and Cathy Schoen, M.S.
The New England Journal of Medicine
Downloaded from on November 4, 2015. For personal use only. No other uses without permission.
Copyright © 2012 Massachusetts Medical Society. All rights reserved.
... One method whereby data collection, analysis, and intervention with behavioral health can more easily scale is through technology. For example, researchers have shown how technology allows practitioners and researchers to collect moment-by-moment data on the responses that people emit throughout their daily lives (e.g., Asch et al., 2012;Mehta et al., 2019). Further, researchers have also shown how technology can be used to collect data on the environment surrounding those responses at a similar moment-by-moment temporal scale (e.g., Bertz et al., 2018; Epstein et al., 2014;Kwan et al., 2018). ...
... These devices are then used to collect data that allows researchers or BHPs to track and analyze patterns in what people are doing, where they are going, and their physiological state. In turn, these data can be used with AI to predict: if and when people will relapse to using drugs after they successfully quit (e.g., Asch et al., 2012;Budney et al., 2019;Dallery et al., 2015), when someone might experience a relapse of cancer following successful treatment and remission (e.g., Good et al., 2018), or when someone might relapse to severe depression and be at-risk of suicide following a successful behavioral intervention (e.g., Carson et al., Ji et al., 2019;Walsh et al., 2017Walsh et al., , 2018. Of note, much of this work has been accomplished without the collaboration of BHPs or researchers who have a robust understanding of the behavioral processes likely to control the recurrence of clinical levels of physiological or behavioral phenomena (e.g., Greer & Shahan, 2019;Liggett et al., 2018;Muething et al., 2022). ...
Full-text available
Artificial intelligence (AI) has begun to impact nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this journal likely work in one or more areas of behavioral health. For readers who work in behavioral health and who are interested in AI, the purpose of this article is to highlight the pervasiveness of AI research being conducted around many facets of behavioral health service delivery. To do this, we first provide a brief overview of some of the areas within AI and the types of problems each area of AI attempts to solve. We then outline the prototypical client journey in behavioral healthcare beginning with diagnosis/assessment and ending with intervention withdrawal or ongoing monitoring. Next, for each stage in the client journey, we highlight several areas that parallel existing behavior analytic practice where researchers have begun to use AI, often to improve the efficiency of service delivery or to learn new things that improve the effectiveness of behavioral health services. Finally, for those whose appetite has been whet for getting involved with AI, we close by describing three roles they might consider trying out and that parallel the three main domains of behavior analysis. These three roles are an AI tool designer (akin to EAB), AI tool implementer (akin to ABA), or AI tool supporter (akin to practice).
... The BMT4me© app intervention was informed by Behavioral Economics (BE) Theory [40,41] and the Pediatric Self-management Model [42]. Stakeholder feedback of wireframes was conducted through a mixed methods usability study and informed the initial development of the app. ...
Full-text available
Medication non-adherence rates in children range between 50% and 80% in the United States. Due to multifaceted outpatient routines, children receiving hematopoietic stem cell transplant (HCT) are at especially high risk of non-adherence, which can be life-threatening. Although digital health interventions have been effective in improving non-adherence in many pediatric conditions, limited research has examined their benefits among families of children receiving HCT. To address this gap, we created the BMT4me© mobile health app, an innovative intervention serving as a "virtual assistant" to send medication-taking reminders for caregivers and to track, in real-time, the child's medication taking, barriers to missed doses, symptoms or side effects, and other notes regarding their child's treatment. In this randomized controlled trial, caregivers will be randomized to either the control (standard of care) group or the intervention (BMT4me© app) group at initial discharge post-HCT. Both groups will receive an electronic adherence monitoring device (i.e., medication event monitoring system "MEMS" cap, Medy Remote Patient Management "MedyRPM" medication adherence box) to store their child's immunosuppressant medication. Caregivers who agree to participate will be asked to complete enrollment, weekly, and monthly parent-proxy measures of their child's medication adherence until the child reaches Day 100 or complete taper from immunosuppression. Caregivers will also participate in a 15 to 30-minute exit interview at the conclusion of the study. Descriptive statistics and correlations will be used to assess phone activity and use behavior over time. Independent samples t-tests will examine the efficacy of the intervention to improve adherence monitoring and reduce readmission rates. The primary expected outcome of this study is that the BMT4me© app will improve the real-time monitoring and medication adherence in children receiving hematopoietic stem cell transplant following discharge, thus improving clinical outcomes.
... Way to Health is an automated information technology platform that integrates wireless devices, randomization, digital messaging, and secure data capture 20,21 . A Fitbit sleep tracker (Flex 2 or Inspire) was used to measure sleep duration in the home setting; this is a single sensor device with a proprietary algorithm used to estimate sleep from locomotor data collected by the accelerometer. ...
Full-text available
Objective: Determine the optimal combination of digital health intervention component settings that increase average sleep duration by ≥30 minutes per weeknight. Methods: Optimization trial using a 25 factorial design. The trial included 2 week run-in, 7 week intervention, and 2 week follow-up periods. Typically developing children aged 9-12y, with weeknight sleep duration <8.5 hours were enrolled (N=97). All received sleep monitoring and performance feedback. The five candidate intervention components (with their settings to which participants were randomized) were: 1) sleep goal (guideline-based or personalized); 2) screen time reduction messaging (inactive or active); 3) daily routine establishing messaging (inactive or active); 4) child-directed loss-framed financial incentive (inactive or active); and 5) caregiver-directed loss-framed financial incentive (inactive or active). The primary outcome was weeknight sleep duration (hours per night). The optimization criterion was: ≥30 minutes average increase in sleep duration on weeknights. Results: Average baseline sleep duration was 7.7 hours per night. The highest ranked combination included the core intervention plus the following intervention components: sleep goal (either setting was effective), caregiver-directed loss-framed incentive, messaging to reduce screen time, and messaging to establish daily routines. This combination increased weeknight sleep duration by an average of 39.6 (95% CI: 36.0, 43.1) minutes during the intervention period and by 33.2 (95% CI: 28.9, 37.4) minutes during the follow-up period. Conclusions: Optimal combinations of digital health intervention component settings were identified that effectively increased weeknight sleep duration. This could be a valuable remote patient monitoring approach to treat insufficient sleep in the pediatric setting.
... Finally, mobile and wearable technology may be able to improve disease outcomes by fundamentally altering patient behavior. This has been termed "automated hovering", and constitutes a significant new horizon for healthcare intervention (Asch et al. 2012) given that a significant majority of patient decisions are made without direct input from a clinician. For example, in one pilot randomized study, a wearable fitness tracker that provided real time biometric data and feedback increased activity and reduced sedentary time in a group at risk for cardiovascular disease (Roberts et al. 2019). ...
Full-text available
Hepatic Encephalopathy (HE) is a critically important complication of chronic liver disease and portal hypertension, but especially in early covert stages remains underdiagnosed and a common cause of hospitalization and morbidity. Defined by often subtle neuropsychiatric changes, significant cognitive deficits have been extensively described. While traditional methods of assessment remain underutilized in practice and subject to significant confounding with other diseases, mobile technology has emerged as a potential future tool to provide simple and dynamic cognitive assessments. This review discusses the proliferation of cognitive assessment tools, describing possible applications in encephalopathy and the challenges such an implementation may face. There are significant potential advantages to assessing cognition in real time in order to aid early detection and intervention and provide a more realistic measurement of real-world function. Despite this, there are issues with reliability, privacy, applicability and more which must be addressed prior to wide proliferation and acceptance for clinical use. Regardless, the rapid uptake of mobile technology in healthcare is likely to have significant implications for the future management of encephalopathy and liver disease at large.
Connected healthcare is a form of health delivery that connects patients and providers through connected health devices, allowing providers to monitor patient behavior and proactively intervene before an adverse event occurs. Unlike the costs, the benefits of connected healthcare in improving patient behavior and health outcomes are usually difficult to determine. In this study, we examine the efficacy of a connected health system that aimed to reduce readmissions through improved medication adherence. Specifically, we study 975 patients with heart disease who received electronic pill bottles that tracked medication adherence. Patients who were nonadherent received active social support that involved different types of feedback, such as text messages and calls. By integrating data on adherence, intervention, and readmission, we aim to (1) investigate the efficacy of connected healthcare in promoting medication adherence, (2) examine the relationship between medication adherence and readmission, and (3) develop a dynamic readmission risk-scoring model that considers medication adherence and use the model to better target nonadherent patients. Our findings suggest that patients are more likely to become adherent when they or their partners receive high levels of intervention that involve personalized feedback and when the intervention is escalated quickly and consistently. We also find that long-term adherence to three common heart medications is strongly associated with reduced readmission risk. Lastly, using counterfactual simulation, we apply the dynamic readmission risk-scoring model to our setting and find that, when using an intervention strategy that prioritizes high-risk patients, we obtain 10% fewer readmissions while using the same effort level from the patient support team. This paper was accepted by Jayashankar Swaminathan, operations management. Funding: The randomized, controlled trial was funded by the Center for Medicare & Medicaid Innovation [Healthcare Innovation Award 1C1CMS331009]. Supplemental Material: The data files are available at .
Cerebrovascular disease (CeVD) is a leading cause of death and disability worldwide. Early detection of behavioral and physiologic changes associated with CeVD may be critical to improving patient outcomes. The growing prevalence of remote monitoring tools, from wearable devices to smartphone applications, which facilitate in situ observation of patients, holds promise for more timely recognition and possible prevention of stroke. The goal of this review was to examine and establish categories of innovation with digital sensors that monitor physiologic and behavioral variables in situ to augment the current CeVD screening and diagnostic processes. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist, a search strategy spanning multiple databases from January 2012 to September 30, 2022, was implemented, aggregating 729 articles, of which 51 (7.0%) met the inclusion criteria. The articles were divided into 2 categories on the basis of their focus: physiologic and behavioral. Physiologic articles were sorted into 1 of the following 6 subcategories according to the signal(s) monitored: motor function, heart rhythm, heart rate, kinematic analysis, physical activity, and blood pressure. Behavioral articles were sorted into the following 3 subcategories: mood, cognitive function, and fatigue. Most studies used a wearable accelerometer, photoplethysmography-enabled smartwatch, or smartphone-based sensors. This scoping review identified disparate methods and conclusions associated with the use of digital sensors for in situ physiologic and behavioral monitoring of patients with CeVD. Although most articles evaluated pilot validation and feasibility trials, the lack of randomized controlled trials was identified as a critical gap specific to this evolving research area.
Objective: To describe the degree of automation in just-in-time, adaptive interventions (JITAIs) assessed in randomized controlled trials (RCTs) in any medical speciality, and to assess the completeness of intervention reporting. Study design and setting: Systematic scoping review. We searched PubMed, PsycINFO, and Web of Science, from 1 January 2019 to 2 March 2021, for reports of RCTs assessing JITAIs. We assessed whether study reports included the minimum information required to replicate the intervention based on JITAI frameworks. We described JITAIs according to their automation level using an established framework (partially, highly, or fully automated), and care workload distribution (requiring work from patients, healthcare professionals [HCPs], both, or neither). Results: We included 88 JITAIs (63%, n=56 supported chronic illness management, 12%, n=11 supported health behavior change). Overall, 77% (n=68) of JITAIs were missing some information required to replicate the intervention (e.g., n=38, 43% inadequately reported the algorithm used to select intervention components). Only fifteen (17%) JITAIs were fully automated and did not require additional work from HCPs nor patients. Of the remaining JITAIs, 36% required work from both patients and HCPs, and 46% required work from either patients or HCPs. Conclusions: Most JITAIs are not fully automated and require work from HCPs and patients.
Full-text available
Sub-optimal adherence to warfarin places millions of patients at risk for stroke and bleeding complications each year. Novel methods are needed to improve adherence for warfarin. We conducted two pilot studies to determine whether a lottery-based daily financial incentive is feasible and improves warfarin adherence and anticoagulation control. Volunteers from the University of Pennsylvania Anticoagulation Management Center who had taken warfarin for at least 3 months participated in either a pilot study with a lottery with a daily expected value of $5 (N = 10) or a daily expected value of $3 (N = 10). All subjects received use of an Informedix Med-eMonitor System with a daily reminder feature. If subjects opened up their pill compartments appropriately, they were entered into a daily lottery with a 1 in 5 chance of winning $10 and a 1 in 100 chance of winning $100 (pilot 1) or a 1 in 10 chance of winning $10 and a 1 in 100 chance of winning $100 (pilot 2). The primary study outcome was proportion of incorrect warfarin doses. The secondary outcome was proportion of INR measurements not within therapeutic range. Within-subject pre-post comparisons were done of INR measurements with comparisons with either historic means or within-subject comparisons of incorrect warfarin doses. In the first pilot, the percent of out-of-range INRs decreased from 35.0% to 12.2% during the intervention, before increasing to 42% post-intervention. The mean proportion of incorrect pills taken during the intervention was 2.3% incorrect pills, compared with a historic mean of 22% incorrect pill taking in this clinic population. Among the five subjects who also had MEMS cap adherence data from warfarin use in our prior study, mean incorrect pill taking decreased from 26% pre-pilot to 2.8% in the pilot. In the second pilot, the time out of INR range decreased from 65.0% to 40.4%, with the proportion of mean incorrect pill taking dropping to 1.6%. A daily lottery-based financial incentive demonstrated the potential for significant improvements in missed doses of warfarin and time out of INR range. Further testing should be done of this approach to determine its effectiveness and potential application to both warfarin and other chronic medications.
Full-text available
Until recently, when anthrax triggered a concern about preparedness in the public health infrastructure, U.S. health policy and health spending had been dominated by a focus on payment for medical treatment. The fact that many of the conditions driving the need for treatment are preventable ought to draw attention to policy opportunities for promoting health. Following a brief review of the determinants of population health-genetic predispositions, social circumstances, environmental conditions, behavioral patterns, and medical care-this paper explores some of the factors inhibiting policy attention and resource commitment to the nonmedical determinants of population health and suggests approaches for sharpening the public policy focus to encourage disease prevention and health promotion.
A 7-year-old girl with a history of recurrent urinary tract infection since the age of 3 years is known to have bilateral, moderately severe (grade III) vesicoureteral reflux. Renal scintigraphy with technetium-99-labeled dimercaptosuccinic acid has revealed bilateral scarring in the upper poles of her kidneys, with more severe scarring on the left kidney than on the right. Despite ongoing antimicrobial prophylaxis, she has recently had another febrile urinary tract infection, which responded well to antibiotic treatment. Radionuclide cystography reveals persistent bilateral, moderately severe vesicoureteral reflux. The patient has no history of constipation or dysfunctional voiding. She is referred to a pediatric urologist, who discusses with the patient and her parents the various treatment options, including endoscopic correction.
Redesigning Employee Health Incentives Starting in 2014, employers will be able to use a portion of employees' health insurance premiums to provide outcome-based wellness incentives to try to cut health care costs. But evidence that such programs work is scant. Lessons from behavioral economics might help.
The American Urological Association established the Vesicoureteral Reflux Guideline Update Committee in July 2005 to update the management of primary vesicoureteral reflux in children guideline. The Panel defined the task into 5 topics pertaining to specific vesicoureteral reflux management issues, which correspond to the management of 3 distinct index patients and the screening of 2 distinct index patients. This report summarizes the existing evidence pertaining to children with diagnosed reflux including those young or older than 1 year without evidence of bladder and bowel dysfunction and those older than 1 year with evidence of bladder and bowel dysfunction. From this evidence clinical practice guidelines were developed to manage the clinical scenarios insofar as the data permit. The Panel searched the MEDLINE(R) database from 1994 to 2008 for all relevant articles dealing with the 5 chosen guideline topics. The database was reviewed and each abstract segregated into a specific topic area. Exclusions were case reports, basic science, secondary reflux, review articles and not relevant. The extracted article to be accepted should have assessed a cohort of children with vesicoureteral reflux and a defined care program that permitted identification of cohort specific clinical outcomes. The reporting of meta-analysis of observational studies elaborated by the MOOSE (Meta-analysis Of Observational Studies in Epidemiology) group was followed. The extracted data were analyzed and formulated into evidence-based recommendations. A total of 2,028 articles were reviewed and data were extracted from 131 articles. Data from 17,972 patients were included in this analysis. This systematic meta-analysis identified increasing frequency of urinary tract infection, increasing grade of vesicoureteral reflux and presence of bladder and bowel dysfunction as unique risk factors for renal cortical scarring. The efficacy of continuous antibiotic prophylaxis could not be established with current data. However, its purported lack of efficacy, as reported in selected prospective clinical trials, also is unproven owing to significant limitations in these studies. Reflux resolution and endoscopic surgical success rates are dependent upon bladder and bowel dysfunction. The Panel then structured guidelines for clinical vesicoureteral reflux management based on the goals of minimizing the risk of acute infection and renal injury, while minimizing the morbidity of testing and management. These guidelines are specific to children based on age as well as the presence of bladder and bowel dysfunction. Recommendations for long-term followup based on risk level are also included. Using a structured, formal meta-analytic technique with rigorous data selection, conditioning and quality assessment, we attempted to structure clinically relevant guidelines for managing vesicoureteral reflux in children. The lack of robust prospective randomized controlled trials limits the strength of these guidelines but they can serve to provide a framework for practice and set boundaries for safe and effective practice. As new data emerge, these guidelines will necessarily evolve.
We compared the development of new renal damage in small children with dilating vesicoureteral reflux randomly allocated to antibiotic prophylaxis, endoscopic treatment or surveillance as the control group. Included in the study were 128 girls and 75 boys 1 to younger than 2 years with grade III-IV reflux. Voiding cystourethrography and dimercapto-succinic acid scintigraphy were done before randomization and after 2 years. Febrile urinary tract infections were recorded during followup. Data analysis was done by the intent to treat principle. New renal damage in a previously unscarred area was seen in 13 girls and 2 boys. Eight of the 13 girls were on surveillance, 5 received endoscopic therapy and none were on prophylaxis (p = 0.0155). New damage was more common in children with than without febrile recurrence (11 of 49 or 22% vs 4 of 152 or 3%, p <0.0001). In boys the rate of new renal damage was low. It was significantly higher in girls and most common in the control surveillance group. There was also a strong association between recurrent febrile UTIs and new renal damage in girls.
The purpose of ureterocystoneostomy to correct vesicoureteral reflux is to thereby prevent recurrent febrile urinary tract infections (UTIs). The objective of this study was to determine the frequency of UTI in adult women who underwent reimplantation as children, with the emphasis on infections during pregnancy. Included in the study were women over 20 years of age who underwent surgery for primary reflux between 1969 and 2004. A total of 392 patients were identified and information on their case history, surgery and follow-up was collected from the medical records. A questionnaire, requesting information on their present state of health, and occurrences of lower or upper UTI since the age of 16 and during any pregnancies, was sent to 337 of these patients. In all, 242 (84%) of the questionnaires were returned. UTIs had occurred in 42% of the women before they had any sexual activity; thereafter the frequency increased to 61%. In 113 of the 282 women, 242 pregnancies were recorded. UTI occurred during 59 pregnancies (24%): 19% lower, 5% upper. Risk factors for UTI during pregnancy were infections as adults or decreased differential renal function (< or = 30%). There is an ongoing risk of UTI in adult women after anti-reflux surgery in childhood. During pregnancy, these women represent a population at risk who should be observed very closely.
This study was undertaken to determine the prevalence of hypertension in children with primary, uncomplicated vesicoureteral reflux (VUR) and to evaluate the relationship between blood pressure (BP), grade and duration of reflux, and renal scarring. Subjects were identified retrospectively during a 17-year period; of 146 subjects who agreed to participate, 129 (88.4%) were female. Mean age at diagnosis was 5.0 years (range, 1 month to 16 years), and at follow-up was 14.4 years (range, 5 months to 21 years). Mean duration of follow-up was 9.6 years. Renal scarring was detected in 34.3% of patients by intravenous pyelogram, ultrasonography, or both. The BP at diagnosis was linearly related to the grade of reflux, but values were not higher than expected norms for age. At follow-up, mean systolic and diastolic BP were at the 41.6 percentile and the 18.7 percentile, respectively. No patient's BP was above the 55th percentile. After a mean follow-up period of 10 years, we conclude that primary, uncomplicated VUR, regardless of the number of documented urinary tract infections, duration and severity of reflux, modality of therapy, presence of renal scarring, and duration of follow-up, is not associated with the development of hypertension. Hypertension does not appear to be a complication of VUR and urinary tract infection unless there is preexisting dysplasia.
Primary vesicoureteral reflux (VUR), one of the principal causes of chronic renal failure (CRF), occurs as a result of two distinct and sex-related mechanisms: congenital renal hypoplasia, which is prevalent in males, and acquired renal scarring in females. We used data from the ItalKid Project, a prospective population-based CRF registry of patients undergoing conservative treatment, to evaluate the gender distribution and severity of primary VUR, the age at diagnosis, and the diagnostic and therapeutic methods adopted in children with CRF. The prevalence of males (77.5%), the severity of VUR (grade IV-V), and the early age at diagnosis (18% prenatally) seem to suggest that congenital renal damage is the major cause of pediatric CRF.