Browsing by Author "Piette, John D"
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- ItemAddressing medication nonadherence by mobile phone: development and delivery of tailored messages.(2014-12-03) Gatwood, Justin; Balkrishnan, Rajesh; Erickson, Steven R; An, Lawrence C; Piette, John D; Farris, Karen BBACKGROUND Medication nonadherence remains a significant public health problem and efforts to improve adherence have shown only limited impact The tailoring of messages has become a popular method of developing communication to influence specific health related behaviors but the development and impact of tailored text messages on medication use is poorly understood OBJECTIVES The aim of this paper is to describe an approach to developing theory based tailored messages for delivery via mobile phone to improve medication adherence among patients with diabetes METHODS Kreuter s five step tailoring process was followed to create tailored messages for mobile phone delivery Two focus group sessions using input from 11 people and expert review of message content were used to adapt the survey instrument on which the messages were tailored and edit the developed messages for the target population RESULTS AND CONCLUSIONS Following established tailoring methods a library of 168 theory driven and 128 medication specific tailored messages were developed and formatted for automated delivery to mobile phones Concepts from the Health Belief Model and Self Determination Theory were used to craft the messages and an algorithm was applied to determine the order and timing of messages with the aim of progressively influencing disease and treatment related beliefs driving adherence to diabetes medication The process described may be applied to future investigations aiming to improve medication adherence in patients with diabetes and the effectiveness of the current messages will be tested in a planned analysis
- ItemDeveloping an automated speech-recognition telephone diabetes intervention.(2008-07-14) Goldman, Roberta E; Sanchez-Hernandez, Maya; Ross-Degnan, Dennis; Piette, John D; Trinacty, Connie Mah; Simon, Steven RMany patients do not receive guideline recommended care for diabetes and other chronic conditions Automated speech recognition telephone outreach to supplement in person physician patient communication may enhance patient care for chronic illness We conducted this study to inform the development of an automated telephone outreach intervention for improving diabetes care among members of a large not for profit health plan
- ItemDiabetes self-management support using mHealth and enhanced informal caregiving.(2014-02-25) Aikens, James E; Zivin, Kara; Trivedi, Ranak; Piette, John DOBJECTIVE To characterize diabetes patient engagement and clinician notifications for an mHealth interactive voice response IVR service DESIGN Observational study METHODS For three to six months VA patients with diabetes received weekly IVR calls assessing health status and self care along with tailored education Patients could enroll with an informal caregiver who received suggestions on self management support Notifications were issued to clinicians when patients reported significant problems RESULTS Patients n 303 participated for a total of 5684 patient weeks during which 84 of calls were completed The odds of call completion decreased over time AOR 0 96 p Under 0 001 and were lower among unmarried patients AOR 0 67 p 0 038 and those who had difficulties with health literacy AOR 0 67 p 0 039 diabetes related distress AOR 0 30 p 0 018 or medication nonadherence AOR 0 57 p 0 002 Twenty one clinician notifications were triggered per 100 patient weeks The odds of notification were higher during the early weeks of the program AOR 0 95 p Under 0 001 and among patients who were older AOR 1 03 p 0 004 or more physically impaired AOR 0 97 p Under 0 001 CONCLUSIONS By providing information that is reliable valid and actionable IVR based mHealth services may increase access to between visit monitoring and diabetes self management support The system detects abnormal glycemia and blood pressure levels that might otherwise go unreported although thresholds for clinician notifications might require adjustment to avoid overloading clinicians Patient engagement might be enhanced by addressing health literacy and psychological distress
- ItemEstablishing an independent mobile health program for chronic disease self-management support in bolivia.(2014-08-28) Piette, John D; Valverde, Helen; Marinec, Nicolle; Jantz, Rachel; Kamis, Kevin; de la Vega, Carlos Lazo; Woolley, Timothy; Pinto, BismarckBACKGROUND Mobile health m health work in low and middle income countries LMICs mainly consists of small pilot programs with an unclear path to scaling and dissemination We describe the deployment and testing of an m health platform for non communicable disease NCD self management support in Bolivia METHODS Three hundred sixty four primary care patients in La Paz with diabetes or hypertension completed surveys about their use of mobile phones health and access to care One hundred sixty five of those patients then participated in a 12 week demonstration of automated telephone monitoring and self management support Weekly interactive voice response IVR calls were made from a platform established at a university in La Paz under the direction of the regional health ministry RESULTS Thirty seven percent of survey respondents spoke indigenous languages at home and 38 had six or fewer years of education Eighty two percent had a mobile phone 45 used text messaging with a standard phone and 9 had a smartphone Smartphones were least common among patients who were older spoke indigenous languages or had less education IVR program participants completed 1007 self management support calls with an overall response rate of 51 IVR call completion was lower among older adults but was not related to patients ethnicity health status or healthcare access IVR health and self care reports were consistent with information reported during in person baseline interviews Patients likelihood of reporting excellent very good or good health versus fair or poor health via IVR increased during program participation and was associated with better medication adherence Patients completing follow up interviews were satisfied with the program with 19 20 95 reporting that they would recommend it to a friend CONCLUSION By collaborating with LMICs m health programs can be transferred from higher resource centers to LMICs and implemented in ways that improve access to self management support among people with NCDs
- ItemHypertension management using mobile technology and home blood pressure monitoring: results of a randomized trial in two low/middle-income countries.(2012-10-15) Piette, John D; Datwani, Hema; Gaudioso, Sofia; Foster, Stephanie M; Westphal, Joslyn; Perry, William; Rodríguez-Saldaña, Joel; Mendoza-Avelares, Milton O; Marinec, NicolleOBJECTIVE Hypertension and other noncommunicable diseases represent a growing threat to low middle income countries LMICs Mobile health technologies may improve noncommunicable disease outcomes but LMICs lack resources to provide these services We evaluated the efficacy of a cloud computing model using automated self management calls plus home blood pressure BP monitoring as a strategy for improving systolic BPs SBPs and other outcomes of hypertensive patients in two LMICs SUBJECTS AND METHODS This was a randomized trial with a 6 week follow up Participants with high SBPs 140 mm Hg if nondiabetic and 130 mm Hg if diabetic were enrolled from clinics in Honduras and Mexico Intervention patients received weekly automated monitoring and behavior change telephone calls sent from a server in the United States plus a home BP monitor At baseline control patients received BP results hypertension information and usual healthcare The primary outcome SBP was examined for all patients in addition to a preplanned subgroup with low literacy or high hypertension information needs Secondary outcomes included perceived health status and medication related problems RESULTS Of the 200 patients recruited 181 90 completed follow up and 117 of 181 had low literacy or high hypertension information needs The median annual income was 2 900 USD and average educational attainment was 6 5 years At follow up intervention patients SBPs decreased 4 2 mm Hg relative to controls 95 confidence interval 9 1 0 7 p 0 09 In the subgroup with high information needs intervention patients average SBPs decreased 8 8 mm Hg 14 2 3 4 p 0 002 Compared with controls intervention patients at follow up reported fewer depressive symptoms p 0 004 fewer medication problems pUnder0 0001 better general health pUnder0 0001 and greater satisfaction with care p 0 004 CONCLUSIONS Automated telephone care management plus home BP monitors can improve outcomes for hypertensive patients in LMICs A cloud computing model within regional telecommunication centers could make these services available in areas with limited infrastructure for patient focused informatics support
- ItemImplementation and barriers to uptake of interactive voice response technology aimed to improve blood pressure control at a large academic medical center.(0000-00-00) Ashjian, Emily J; Yoo, Anne; Piette, John D; Choe, Hae Mi; Thompson, Amy NOBJECTIVES Blood pressure control among patients with hypertension is a widely recognized quality metric but many large health systems fail to reach targets set by the Healthcare Effectiveness Data and Information Set We developed an interactive voice response IVR system called the Mobile You Blood Pressure Program at a large academic medical center and linked it to the health system s electronic health record EHR The goal of the program was to capture home blood pressure readings in the EHR and to alert ambulatory care clinical pharmacists automatically of readings below or above clinical thresholds through direct messaging in the EHR The goal of this report is to describe implementation of IVR initial patient participation rates and pharmacist identified barriers to patient enrollment SETTING Ambulatory care clinical pharmacist specialists practice in 14 clinics in family medicine and internal medicine at Michigan Medicine an academic health system serving more than 24 000 patients with a diagnosis of hypertension PRACTICE DESCRIPTION This study describes implementation and initial patient enrollment in IVR linked to the EHR for home blood pressure monitoring EVALUATION We tracked the number of hypertensive patients enrolled and IVR call completion rates between September 2017 and February 2018 We also assessed pharmacist identified barriers to patient enrollment during two separate 2 week intervals in January and February 2018 RESULTS Between September 1 2017 and February 28 2018 a total of 71 patients were enrolled from 14 clinics Patients were scheduled for 1 3 IVR calls per week focusing on medication adherence and blood pressure control A total of 936 IVR phone calls were made with 488 52 calls completed Access to a validated home blood pressure monitor was the largest pharmacist identified barrier to patient enrollment CONCLUSIONS The IVR Mobile You Blood Pressure Program represents a new application of digital technology within our health system Pharmacist identified barriers to patient participation included access to a validated home blood pressure monitor
- ItemImprovements in illness self-management and psychological distress associated with telemonitoring support for adults with diabetes.(2015-03-11) Aikens, James E; Rosland, Ann-Marie; Piette, John DOBJECTIVE The objective of this observational open label trial was to characterize changes in diabetes self management and psychological distress associated with a mobile health mHealth interactive voice response IVR self management support program METHODS For 3 6 months 301 patients with diabetes received weekly IVR calls assessing health status and self care and providing tailored pre recorded self management support messages Patients could participate together with an informal caregiver who received suggestions on self management support and patients clinicians were notified automatically when patients reported significant problems RESULTS Patients completed 84 of weekly calls providing 5682 patient weeks of data Thirty nine percent participated with an informal caregiver Outcome analyses adjusted for study design factors and sociodemographics indicated significant pre post improvement in medication adherence physical functioning depressive symptoms and diabetes related distress all p values Under0 001 Analyses of self management problems indicated that as the intervention proceeded there were significant improvements in patients IVR reported frequency of weekly medication adherence SMBG performance checking feet and frequency of abnormal self monitored blood glucose readings all p values Under0 001 CONCLUSIONS We conclude that the combined program of automated telemonitoring clinician notification and informal caregiver involvement was associated with consistent improvements in medication adherence diabetes self management behaviors physical functioning and psychological distress A randomized controlled trial is needed to verify these encouraging findings
- ItemImproving heart failure self-management support by actively engaging out-of-home caregivers: results of a feasibility study.(2008-02-07) Piette, John D; Gregor, Mary Ann; Share, David; Heisler, Michele; Bernstein, Steven J; Koelling, Todd; Chan, PaulThe benefits of heart failure HF care management have been demonstrated yet health systems are often unable to meet patients needs for support between outpatient visits Informal care provided by family or friends is a low cost and potentially effective adjunct to care management services The authors evaluated the feasibility of augmenting HF care management with weekly automated assessment and behavior change calls to patients feedback via the Internet to an out of home informal caregiver or CarePartner CP and faxes to the patient s health care team The program included 52 HF patient CP pairs participating for an average of 12 weeks Patients completed 586 assessments 92 completion rate and reported problems that might otherwise have gone unidentified At follow up 75 had made changes in their self care as a result of the intervention The CP program may extend the impact of HF telemonitoring beyond what care management programs can realistically deliver
- ItemMaximizing the value of mobile health monitoring by avoiding redundant patient reports: prediction of depression-related symptoms and adherence problems in automated health assessment services.(2013-07-08) Piette, John D; Sussman, Jeremy B; Pfeiffer, Paul N; Silveira, Maria J; Singh, Satinder; Lavieri, Mariel SBACKGROUND Interactive voice response IVR calls enhance health systems ability to identify health risk factors thereby enabling targeted clinical follow up However redundant assessments may increase patient dropout and represent a lost opportunity to collect more clinically useful data OBJECTIVE We determined the extent to which previous IVR assessments predicted subsequent responses among patients with depression diagnoses potentially obviating the need to repeatedly collect the same information We also evaluated whether frequent ie weekly IVR assessment attempts were significantly more predictive of patients subsequent reports than information collected biweekly or monthly METHODS Using data from 1050 IVR assessments for 208 patients with depression diagnoses we examined the predictability of four IVR reported outcomes moderate severe depressive symptoms score 10 on the PHQ 9 fair poor general health poor antidepressant adherence and days in bed due to poor mental health We used logistic models with training and test samples to predict patients IVR responses based on their five most recent weekly biweekly and monthly assessment attempts The marginal benefit of more frequent assessments was evaluated based on Receiver Operator Characteristic ROC curves and statistical comparisons of the area under the curves AUC RESULTS Patients reports about their depressive symptoms and perceived health status were highly predictable based on prior assessment responses For models predicting moderate severe depression the AUC was 0 91 95 CI 0 89 0 93 when assuming weekly assessment attempts and only slightly less when assuming biweekly assessments AUC 0 89 CI 0 87 0 91 or monthly attempts AUC 0 89 CI 0 86 0 91 The AUC for models predicting reports of fair poor health status was similar when weekly assessments were compared with those occurring biweekly P value for the difference 11 or monthly P 81 Reports of medication adherence problems and days in bed were somewhat less predictable but also showed small differences between assessments attempted weekly biweekly and monthly CONCLUSIONS The technical feasibility of gathering high frequency health data via IVR may in some instances exceed the clinical benefit of doing so Predictive analytics could make data gathering more efficient with negligible loss in effectiveness In particular weekly or biweekly depressive symptom reports may provide little marginal information regarding how the person is doing relative to collecting that information monthly The next generation of automated health assessment services should use data mining techniques to avoid redundant assessments and should gather data at the frequency that maximizes the value of the information collected
- ItemMobile health monitoring to characterize depression symptom trajectories in primary care.(2015-02-24) Pfeiffer, Paul N; Bohnert, Kipling M; Zivin, Kara; Yosef, Matheos; Valenstein, Marcia; Aikens, James E; Piette, John DBACKGROUND Classification of depression severity can guide treatment decisions This study examined whether using repeated mobile health assessments to determine symptom trajectories is a potentially useful method for classifying depression severity METHODS 344 primary care patients with depression were identified and recruited as part of a program of mobile health symptom monitoring and self management support Depression symptoms were measured weekly via interactive voice response IVR calls using the Patient Health Questionnaire PHQ 9 Trajectory analysis of weekly IVR PHQ 9 scores from baseline through week 6 was used to subgroup patients according to similar trajectories Multivariable linear regression was used to determine whether the trajectories predicted 12 week PHQ 9 scores after adjusting for baseline and 6 week PHQ 9 scores RESULTS The optimal trajectory analysis model included 5 non intersecting trajectories The subgroups of patients assigned to each trajectory had mean baseline PHQ 9s of 19 7 14 5 9 5 5 0 and 2 0 and respective mean decreases in PHQ 9s over six weeks of 3 2 0 3 6 2 3 and 1 9 In regression analyses each trajectory significantly predicted 12 week PHQ 9 scores using the modal trajectory as a reference after adjusting for both baseline and 6 week PHQ 9 scores LIMITATIONS Treatment history was unknown findings may not be generalizable to new episodes of treatment CONCLUSIONS Depression symptom trajectories based on mobile health assessments are predictive of future depression outcomes even after accounting for typical assessments at baseline and a single follow up time point Approaches to classify patients disease status that involve multiple repeated assessments may provide more accurate and useful information for depression management compared to lower frequency monitoring
- ItemOut-of-home informal support important for medication adherence, diabetes distress, hemoglobin A1c among adults with type 2 diabetes.(0000-00-00) Mayberry, Lindsay S; Piette, John D; Lee, Aaron A; Aikens, James EAdults with type 2 diabetes mellitus T2DM often receive self management support from adult children siblings or close friends residing outside of their home However the role of out of home support in patients self management and well being is unclear Patients N 313 with HbA1c 7 5 were recruited from community primary care clinics for a mobile health intervention trial and identified an out of home informal support person herein called a CarePartner 38 also had an in home supporter We tested cross sectional adjusted associations between CarePartner relationship characteristics and patients self management diabetes distress and HbA1c and whether having an in home supporter modified these associations Greater CarePartner closeness was associated with a greater odds of perfect medication adherence AOR 1 19 p 029 more fruit vegetable intake 0 14 p 018 and lower diabetes distress 0 14 p 012 More frequent CarePartner contact was associated with better HbA1c among patients with an in home supporter but with worse HbA1c among patients without an in home supporter interaction 0 45 p 005 Emotional closeness with a CarePartner may be important for supporting T2DM self management and reducing diabetes distress CarePartners may appropriately engage more frequently when patients with no in home supporter have poorly controlled diabetes
- ItemThe potential impact of intelligent systems for mobile health self-management support: Monte Carlo simulations of text message support for medication adherence.(2015-02-20) Piette, John D; Farris, Karen B; Newman, Sean; An, Larry; Sussman, Jeremy; Singh, SatinderBACKGROUND Mobile health mHealth services cannot easily adapt to users unique needs PURPOSE We used simulations of text messaging SMS for improving medication adherence to demonstrate benefits of interventions using reinforcement learning RL METHODS We used Monte Carlo simulations to estimate the relative impact of an intervention using RL to adapt SMS adherence support messages in order to more effectively address each non adherent patient s adherence barriers e g forgetfulness versus side effect concerns SMS messages were assumed to improve adherence only when they matched the barriers for that patient Baseline adherence and the impact of matching messages were estimated from literature review RL SMS was compared in common scenarios to simple reminders random messages and standard tailoring RESULTS RL could produce a 5 14 absolute improvement in adherence compared to current approaches When adherence barriers are not accurately reported RL can recognize which barriers are relevant for which patients When barriers change RL can adjust message targeting RL can detect when messages are sent too frequently causing burnout CONCLUSIONS RL systems could make mHealth services more effective
- ItemA preliminary study of a cloud-computing model for chronic illness self-care support in an underdeveloped country.(2011-05-13) Piette, John D; Mendoza-Avelares, Milton O; Ganser, Martha; Mohamed, Muhima; Marinec, Nicolle; Krishnan, SheilaBACKGROUND Although interactive voice response IVR calls can be an effective tool for chronic disease management many regions of the world lack the infrastructure to provide these services PURPOSE This study evaluated the feasibility and potential impact of an IVR program using a cloud computing model to improve diabetes management in Honduras METHODS A single group pre post study was conducted between June and August 2010 The telecommunications infrastructure was maintained on a U S server and calls were directed to patients cell phones using VoIP Eighty five diabetes patients in Honduras received weekly IVR disease management calls for 6 weeks with automated follow up e mails to clinicians and voicemail reports to family caregivers Patients completed interviews at enrollment and a 6 week follow up Other measures included patients glycemic control HbA1c and data from the IVR calling system RESULTS A total of 53 of participants completed at least half of their IVR calls and 23 of participants completed 80 or more Higher baseline blood pressures greater diabetes burden greater distance from the clinic and better medication adherence were related to higher call completion rates Nearly all participants 98 reported that because of the program they improved in aspects of diabetes management such as glycemic control 56 or foot care 89 Mean HbA1c s decreased from 10 0 at baseline to 8 9 at follow up pUnder0 01 Most participants 92 said that if the service were available in their clinic they would use it again CONCLUSIONS Cloud computing is a feasible strategy for providing IVR services globally IVR self care support may improve self care and glycemic control for patients in underdeveloped countries
- ItemResponse to letter with regard to our paper "Engagement with automated patient monitoring and self-management support calls": experience with a thousand chronically ill patients.(2013-10-16) Piette, John D; Rosland, Ann-Marie; Marinec, Nicolle S; Striplin, Dana; Bernstein, Steven J; Silveira, Maria J
- ItemRethinking the frequency of between-visit monitoring for patients with diabetes.(2014-05-14) Piette, John D; Aikens, James E; Rosland, Ann M; Sussman, Jeremy BBACKGROUND Health systems increasingly look to mobile health tools to monitor patients cost effectively between visits The frequency of assessment services such as interactive voice response IVR calls is typically arbitrary and no approaches have been proposed to tailor assessment schedules based on evidence regarding which measures actually provide new information about patients status METHODS We analyzed longitudinal data from over 5000 weekly IVR monitoring calls to 298 diabetes patients using logistic models to determine the predictability of IVR reported physiological results perceived health indicators and self care behaviors We also determined the implications for assessment burden and problem detection of omitting assessment items that had no more than a 5 predicted probability of a problem report RESULTS Assuming weekly IVR assessments episodes of hyperglycemia were difficult to predict area under the curve AUC 69 7 95 confidence interval CI 50 2 89 2 based on patients prior assessment responses Hypoglycemic symptoms and fair poor perceived health were more predictable and self care behaviors such as problems with medication adherence AUC 92 1 95 CI 89 6 94 6 and foot care AUC 98 4 95 CI 97 0 99 8 were highly predictable Even if patients were only asked about foot inspection behavior when they had 5 chance of a problem report 94 of foot inspection assessments could be omitted while still identifying 91 of reported problems CONCLUSIONS Mobile health monitoring systems could be made more efficient by taking patients reporting history into account Avoiding redundant information requests could make services more patient centered and might increase engagement Time saved by decreasing redundancy could be better spent educating patients or assessing other clinical problems