Dataset Information

Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling.

ABSTRACT: BACKGROUND:mHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics. OBJECTIVE:To determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting. METHODS:We prospectively studied a patient-facing electronic touch-tablet asthma questionnaire deployed as part of the Electronic Asthma Management System. We describe tablet uptake and completion rates and corresponding predictor models for these behaviors. RESULTS:The tablet was offered to and accepted by patients in 891/1715 (52.0%) visits. Patients refused the tablet in 33.0% (439/1330) visits in which it was successfully offered. Patients aged older than 65 years of age (odds ratio [OR] 2.30, 95% CI 1.33-3.95) and with concurrent chronic obstructive pulmonary disease (OR 2.22, 95% CI 1.05-4.67) were more likely to refuse the tablet, and those on an asthma medication (OR 0.55, 95% CI 0.30-0.99) were less likely to refuse it. Once accepted, the questionnaire was completed in 784/891 (88.0%) instances, with those on an asthma medication (OR 0.53, 95% CI 0.32-0.88) being less likely to leave it incomplete. CONCLUSIONS:Older age predicted initial tablet refusal but not tablet questionnaire completion, suggesting that perceptions of mHealth among older adults may negatively impact uptake, independent of usability. The influence of being on an asthma medication suggests that disease severity may also mediate mHealth acceptance. Although use of mHealth questionnaires is growing rapidly across health care settings and diseases, few studies describe their real-world acceptance and its predictors. Our results should be complemented by qualitative methods to identify barriers and enablers to uptake and may inform technological and implementation strategies to drive successful usage.

SUBMITTER: Kouri A

PROVIDER: S-EPMC7532461 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling.

Kouri Andrew A Yamada Janet J Sale Joanna E M JEM Straus Sharon E SE Gupta Samir S

Journal of medical Internet research 20200918 9

<h4>Background</h4>mHealth tablet-based interventions are increasingly being studied and deployed in various health care settings, yet little knowledge exists regarding patient uptake and acceptance or how patient demographics influence these important implementation metrics.<h4>Objective</h4>To determine which factors influence the uptake and successful completion of an mHealth tablet questionnaire by analyzing its implementation in a primary care setting.<h4>Methods</h4>We prospectively studie ...[more]

PMID: 32945779

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Project description:BackgroundAsthma exacerbation leading to emergency department (ED) visit is prevalent, an indicator of poor control of asthma, and is a potentially preventable clinical outcome.ObjectiveWe propose to utilize multiple data elements available in electronic medical records (EMRs) and claims database to create separate algorithms with high validity for clinical and research purposes to identify asthma exacerbation-related ED visit among the general population.MethodsWe performed a retrospective study with inclusion criteria of patients aged 4 to 40 years, a visit to Geisinger ED from January 1, 2006, to October 28, 2013, with asthma on their problem list. Different electronic data elements including chief complaints, vitals, season, smoking, medication use, and discharge diagnoses were obtained to create the algorithm. A stratified random sample was generated to select the charts for review. Chart review was performed to classify patients with asthma-related ED visit, that is, the gold standard. Two reviewers performed the chart review and validation was done on a small subset.ResultsThere were 966 eligible ED visits in the EMR sample and 731 in the claims sample. Agreement between reviewers was 95.45% and kappa statistic was 0.91. Mean age of the EMR sample was 22 years, and mostly white (93%). Multiple models conventionally used in studies were evaluated and the final model chosen included principal diagnosis, bronchodilator, and steroid use for both algorithms, chief complaints for EMR, and secondary diagnosis for claims. Area under the curve was 0.93 (95% confidence interval: 0.91-0.94) and 0.94 (0.93-0.96), respectively, for EMR and claims data, with positive predictive value of?>?94%. The algorithms are visually presented using nomograms.ConclusionWe were able to develop two separate algorithms for EMR and claims to identify asthma exacerbation-related ED visit with excellent diagnostic ability and varying discrimination threshold for clinical and research purposes.

Project description:BACKGROUND:Regular primary care visits may allow an opportunity to deliver high-value, proactive care. However, no previous study has examined whether more temporally regular primary care visits predict better outcomes. OBJECTIVE:To examine the relationship between the temporal regularity of primary care (PC) visits and outcomes. DESIGN:Retrospective cohort study. PARTICIPANTS:We used Medicare claims for 378,862 fee-for-service Medicare beneficiaries, who received PC at 1328 federally qualified health centers from 2010 to 2014. MAIN MEASURES:We created five beneficiary groups based upon their annual number of PC visits. We further subdivided those groups according to whether PC visits occurred with more or less regularity than the median value. We compared these 10 subgroups on three outcomes, adjusting for beneficiary characteristics: emergency department (ED) visits, hospitalizations, and total Medicare expenditures. We also aggregated to the clinic level and divided clinics into tertiles of more, less, and similarly regular to predicted. We compared these three groups of clinics on the same three outcomes of care. KEY RESULTS:Within each visit frequency group, beneficiaries in the subgroup with fewer regular visits had more ED visits, more hospitalizations, and higher costs. Among beneficiaries with the most frequent PC visits, the less regular subgroup had more ED visits (1.70 vs. 1.31 per person-year), more hospitalizations (0.69 vs. 0.57), and greater Medicare expenditures ($20,731 vs. $17,430, p?<?0.001 for all comparisons). Clinics whose PC visits were more regular than predicted also had better outcomes than other clinics, although the effect sizes were smaller. CONCLUSIONS:Temporal patterns of PC visits are correlated with outcomes, even among beneficiaries who appear otherwise similar. Measuring the temporal regularity of PC visits may be useful for identifying beneficiaries at risk for adverse events, and as a barometer for and an impetus to clinic-level quality improvement.

Project description:ImportanceVideo or telephone telemedicine can offer patients access to a clinician without arranging for transportation or spending time in a waiting room, but little is known about patient characteristics associated with choosing between telemedicine or office visits.ObjectiveTo examine patient characteristics associated with choosing a telemedicine visit vs office visit with the same primary care clinicians.Design, setting, and participantsThis cross-sectional study included data from 1 131 722 patients who scheduled a primary care appointment through the Kaiser Permanente Northern California patient portal between January 1, 2016, and May 31, 2018. All completed primary care appointments booked via the patient portal were identified. Only index visits without any other clinical visits within 7 days were included to define a relatively distinct patient-initiated care-seeking episode. Visits for routine physical, which are not telemedicine-eligible, were excluded. Data were analyzed from July 1, 2018, to December 31, 2019.Main outcomes and measuresPatient choice between an office, video, or telephone visit. Relative risk ratios (RRRs) for patient sociodemographic characteristics (age, sex, race/ethnicity, neighborhood socioeconomic status, language preference), technology access (neighborhood residential internet, mobile portal use), visiting the patient's own personal primary care clinician, and in-person visit barriers (travel-time, parking, cost-sharing), associated with choice of video or telephone telemedicine (vs office visit).ResultsOf 2 178 440 patient-scheduled primary care visits scheduled by 1 131 722 patients, 86% were scheduled as office visits and 14% as telemedicine visits, with 7% of the telemedicine visits by video. Choosing telemedicine was statistically significantly associated with patient sociodemographic characteristics. For example, patients aged 65 years and over were less likely than patients aged 18 to 44 years to choose telemedicine (RRR, 0.24; 95% CI, 0.22-0.26 for video visit; RRR 0.55; 95% CI, 0.54-0.57 for telephone visit). Choosing telemedicine was also statistically significantly associated with technology access (patients living in a neighborhood with high rates of residential internet access were more likely to choose a video visit than patients whose neighborhoods had low internet access: RRR, 1.10; 95% CI, 1.06-1.14); as well as in-person visit barriers (patients whose clinic had a paid parking structure were more likely to choose a telemedicine visit than patients whose facility had free parking: RRR, 1.70; 95% CI, 1.41-2.05 for video visit; and RRR, 1.73, 95% CI, 1.61-1.86 for telephone visit).Conclusions and relevanceIn this cross-sectional study, patients usually chose an in-person visit when scheduling an appointment online through the portal. Telemedicine may offer the potential to reach vulnerable patient groups and improve access for patients with transportation, parking, or cost barriers to clinic visits.

Project description:ImportanceMedical practices increasingly allow patients to schedule their own visits through online patient portals, yet little is known about who adopts direct scheduling or how this service is used.ObjectiveTo determine patient and visit characteristics associated with direct scheduling, visit patterns, and potential implications for access and continuity in the primary care setting.Design, setting, and participantsThis cross-sectional study used electronic health record (EHR) data from 17 adult primary care practices in a large academic medical center in the Boston, Massachusetts, area. Participants included patients 18 years or older who were attributed in the EHR to an active primary care physician at 1 of the included primary care practices, were enrolled in the patient portal, and had at least 1 visit to 1 of these practices between March 1, 2018, and March 1, 2019, the period of analysis. Data were analyzed from October 25, 2019, to April 14, 2020.Main outcomes and measuresAdoption of direct scheduling, defined as at least 1 use during the study period. Usual scheduling was defined as scheduling with clinic staff by telephone or in person.ResultsWe examined 134 225 completed visits by 62 080 patients (mean [SD] age, 51.1 [16.4] years, 37 793 [60.9%] women) attributed to 140 primary care physicians at 17 primary care practices. A total of 5020 patients (8.1% [95% CI, 7.9%-8.3%]) adopted direct scheduling, with an age range of 18 to 95 years. Compared with nonadopters in the same practices, adopters were younger (adjusted odds ratio [AOR] per additional year, 0.98 [95% CI, 0.98-0.99]) and were more likely to be White (AOR, 1.09 [95% CI, 1.01-1.17]) and commercially insured (AOR vs uninsured, 1.40 [95% CI, 1.11-1.76]) and to have more comorbidities (AOR per additional comorbidity, 1.07 [95% CI, 1.04-1.11]). Compared with usually scheduled visits, directly scheduled visits were more likely to be for general medical examinations (1979 visits [36.7%] vs 26 519 visits [21.9%]; P < .001) and with one's own primary care physician (5267 visits [95.2%] vs 94 634 visits [73.5%]; P < .001).Conclusions and relevanceThese findings suggest that direct scheduling was associated with greater primary care continuity. Early adopters were more likely to be young, White, and commercially insured, and to the extent these differences persist as direct scheduling is used more widely, this service may widen socioeconomic disparities in primary care access.

Project description:To investigate the performance of parent-reported data in identifying physician-confirmed asthma.Validation study using linkage between the Avon Longitudinal Study of Parents and Children (ALSPAC) and electronic patient records held within the General Practice Research Database (GPRD).Participants were those eligible to participate in ALSPAC who also had a record in the GPRD; this included 765 individuals, just under 4% of ALSPAC-eligible participants. The analysis was based on 141 participants with complete parent-reported asthma data.The main GPRD outcome measure was whether a child had a diagnosis of asthma before they were nine. Parent-reported measures were doctor diagnosis of asthma (before mean age 7.5 years), various outcomes based on wheezing and breathlessness recorded longitudinally between 6 months and 8.5 years. Secondary outcomes were bronchial hyper-responsiveness (BHR), forced expiratory volume in 1 s/forced vital capacity ratio and skin prick test responses.Among the 141 participants with complete parent-reported data, 26 (18%) had an asthma diagnosis before age nine. Using general practitioner (GP)-recorded asthma as the gold standard, the question 'Has a doctor ever diagnosed your child with asthma?' was both sensitive (88.5%) and specific (95.7%). 'Ever wheezed' had the highest sensitivity (100%) but low specificity (60%). More specific definitions were obtained by restricting to those who had wheezed on more than one occasion, experienced frequent wheeze and/or wheezed after the age of 3, but these measures had low sensitivities. BHR only identified 50% of those with a GP-recorded diagnosis.Parental reports of a doctor's diagnosis agree well with a GP-recorded diagnosis. High specificity for asthma can be achieved by using detailed wheezing questions, although these definitions are likely to exclude mild cases of asthma. Our study shows that linkage between observational studies and electronic patient records has the potential to enhance epidemiological research.

Project description:BackgroundRemote monitoring of cardiac implantable electronic devices (CIEDs) has demonstrated substantial benefits. Treatment guidelines have therefore endorsed its use and is being increasingly adopted in the clinical setting, but the level of satisfaction they convey remains still unknown. We developed and validated a questionnaire to measure patient satisfaction with remote monitoring using Medtronic CareLink® Network and assessed its internal reliability and dimensional validity.MethodsAfter a thorough literature review, cognitive debriefing of 18 patients, and an expert panel discussion, a 30-item instrument was proposed and grouped into 5 dimensions (items): 1- Information on cardiac condition (3), 2- Device convenience (3), 3- Transmission process (6), 4- Satisfaction with medical monitoring (8), and 5- General opinions (10). Correlation with the visual analog scale (VAS), overall health related quality of life (HRQoL) measured by the EuroQoL-5D accompanied by the VAS as well as with the Medical Outcomes Study (MOS) SF-36 were assessed. Psychometric properties, exploratory factor analysis and a second order confirmatory factor analysis (a hierarchical CFA with a general common factor explaining the relations between the first order common factors, See Figure 1) were estimated. Models were assessed based on item loading size, sign and statistical significance, and goodness-of-fit statistics.ResultsA total of 186 patients (77% male) with a mean age of 66.03 (SD?=?13.94) years were assessed. 48% had implantable cardioverter-defibrillators, 24% had pacemakers, and 29% had cardiac resynchronization therapy devices. An overall Cronbach's ??=?0.893 was achieved, with acceptable reliabilities for isolated dimensions. Correlations with corresponding VAS scales were meaningful and significant (p?<?0.01). The second order factor solution yielded good goodness-of-fit indexes (?2/df?=?1.44, CFI?=?0.96, TLI?=?0.95, RMSEA?=?0.05). Satisfaction with remote monitoring was not related to HRQoL (r?<?0.05), except for the correlation between the SF-36 mental component and the information on cardiac condition dimension (r?=?0.263, p?<?0.001).ConclusionsThe 30-item questionnaire showed good reliability and validity to assess satisfaction with remote monitoring in patients with CIEDs.

Dataset Information

Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling.

Publications

Primary Care Pre-Visit Electronic Patient Questionnaire for Asthma: Uptake Analysis and Predictor Modeling.

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