Experience with decision support system and comfort with topic predict clinicians’ responses to alerts and reminders

Objective Clinicians at our institution typically respond to about half of the prompts they are given by the clinic’s computer decision support system (CDSS). We sought to examine factors associated with clinician response to CDSS prompts as part of a larger, ongoing quality improvement effort to optimize CDSS use. Methods We examined patient, prompt, and clinician characteristics associated with clinician response to decision support prompts from the Child Health Improvement through Computer Automation (CHICA) system. We asked pediatricians who were nonusers of CHICA to rate decision support topics as “easy” or “not easy” to discuss with patients and their guardians. We analyzed these ratings and data, from July 1, 2009 to January 29, 2013, utilizing a hierarchical regression model, to determine whether factors such as comfort with the prompt topic and the length of the user’s experience with CHICA contribute to user response rates. Results We examined 414 653 prompts from 22 260 patients. The length of time a clinician had been using CHICA was associated with an increase in their prompt response rate. Clinicians were more likely to respond to topics rated as “easy” to discuss. The position of the prompt on the page, clinician gender, and the patient’s age, race/ethnicity, and preferred language were also predictive of prompt response rate. Conclusion This study highlights several factors associated with clinician prompt response rates that could be generalized to other health information technology applications, including the clinician’s length of exposure to the CDSS, the prompt’s position on the page, and the clinician’s comfort with the prompt topic. Incorporating continuous quality improvement efforts when designing and implementing health information technology may ensure that its use is optimized

Physician Intervention to Positive Depression Screens Among Adolescents in Primary Care

Purpose The objective of this study was to determine the effectiveness of computer-based screening and physician feedback to guide adolescent depression management within primary care. Methods We conducted a prospective cohort study within two clinics of the computer-based depression screening and physician feedback algorithm among youth aged 12–20 years between October 2014 and October 2015 in Marion County (Indianapolis), Indiana. Results Our sample included 2,038 youth (51% female; 60% black; mean age = 14.6 years [standard deviation = 2.1]). Over 20% of youth screened positive for depression on the Patient Health Questionnaire-2 and 303 youth (14.8%) screened positive on the Patient Health Questionnaire-9 (PHQ-9). The most common follow-up action by physicians was a referral to mental health services (34.2% mild, 46.8% moderate, and 72.2% severe range). Almost 11% of youth in the moderate range and 22.7% of youth in the severe range were already prescribed a selective serotonin reuptake inhibitor. When predicting mental health service referral, significant predictors in the multivariate analysis included clinic site (40.2% vs. 73.9%; p < .0001) and PHQ-9 score (severe range 77.8% vs. mild range 47.5%; p < .01). Similarly, when predicting initiation of selective serotonin reuptake inhibitors, only clinic site (28.6% vs. 6.9%; p < .01) and PHQ-9 score (severe range 46.7% vs. moderate range 10.6%; p < .001) were significant. Conclusions When a computer-based decision support system algorithm focused on adolescent depression was implemented in two primary care clinics, a majority of physicians utilized screening results to guide clinical care

A six-year repeated evaluation of computerized clinical decision support system user acceptability

OBJECTIVE: Long-term acceptability among computerized clinical decision support system (CDSS) users in pediatrics is unknown. We examine user acceptance patterns over six years of our continuous computerized CDSS integration and updates. MATERIALS AND METHODS: Users of Child Health Improvement through Computer Automation (CHICA), a CDSS integrated into clinical workflows and used in several urban pediatric community clinics, completed annual surveys including 11 questions covering user acceptability. We compared responses across years within a single healthcare system and between two healthcare systems. We used logistic regression to assess the odds of a favorable response to each question by survey year, clinic role, part-time status, and frequency of CHICA use. RESULTS: Data came from 380 completed surveys between 2011 and 2016. Responses were significantly more favorable for all but one measure by 2016 (OR range 2.90-12.17, all p < 0.01). Increasing system maturity was associated with improved perceived function of CHICA (OR range 4.24-7.58, p < 0.03). User familiarity was positively associated with perceived CDSS function (OR range 3.44-8.17, p < 0.05) and usability (OR range 9.71-15.89, p < 0.01) opinions. CONCLUSION: We present a long-term, repeated follow-up of user acceptability of a CDSS. Favorable opinions of the CDSS were more likely in frequent users, physicians and advanced practitioners, and full-time workers. CHICA acceptability increased as it matured and users become more familiar with it. System quality improvement, user support, and patience are important in achieving wide-ranging, sustainable acceptance of CDSS

Unexplained Practice Variation in Primary Care Providers' Concern for Pediatric Obstructive Sleep Apnea

Objective To examine primary care provider (PCP) screening practice for obstructive sleep apnea (OSA) and predictive factors for screening habits. A secondary objective was to describe the polysomnography (PSG) completion proportion and outcome. We hypothesized that both provider and child health factors would predict PCP suspicion of OSA. Methods A computer decision support system that automated screening for snoring was implemented in five urban primary care clinics in Indianapolis, Indiana. We studied 1086 snoring children between 1 and 11 years seen by 26 PCPs. We used logistic regression to examine the association between PCP suspicion of OSA and child demographics, child health characteristics, provider characteristics, and clinic site. Results PCPs suspected OSA in 20% of snoring children. Factors predicting PCP concern for OSA included clinic site (p < .01; OR=0.13), Spanish language (p < .01; OR=0.53), provider training (p=.01; OR=10.19), number of training years (p=.01; OR=4.26) and child age (p<.01), with the youngest children least likely to elicit PCP concern for OSA (OR=0.20). No patient health factors (e.g., obesity) were significantly predictive. Proportions of OSA suspicion were variable between clinic sites (range 6% to 28%) and between specific providers (range 0% to 63%). Of children referred for PSG (n=100), 61% completed the study. Of these, 67% had OSA. Conclusions Results suggest unexplained small area practice variation in PCP concern for OSA amongst snoring children. It is likely that many children at-risk for OSA remain unidentified. An important next step is to evaluate interventions to support PCPs in evidence-based OSA identification

The use of telemonitoring in managing the COVID pandemic:a pilot implementation study

BACKGROUND: Most people with COVID-19 self-manage at home. However, the condition can deteriorate quickly, and some people may develop serious hypoxia with relatively few symptoms. Early identification of deterioration allows effective management with oxygen and steroids. Telemonitoring of symptoms and physiological signs may facilitate this. OBJECTIVE: The aim of this study was to design, implement, and evaluate a telemonitoring system for people with COVID-19 who are self-managing at home and are considered at significant risk of deterioration. METHODS: A multidisciplinary team developed a telemonitoring protocol using a commercial platform to record symptoms, pulse oximetry, and temperature. If symptoms or physiological measures breached targets, patients were alerted and asked to phone for an ambulance (red alert) or for advice (amber alert). Patients attending COVID-19 assessment centers, who were considered fit for discharge but at risk of deterioration, were shown how to use a pulse oximeter and the monitoring system, which they were to use twice daily for 2 weeks. Patients could interact with the system via app, SMS, or touch-tone phone. Written guidance on alerts was also provided. Following consent, patient data on telemonitoring usage and alerts were linked to data on the use of service resources. Subsequently, patients who had either used or not used the telemonitoring service, including those who had not followed advice to seek help, agreed to brief telephone interviews to explore their views on, and how they had interacted with, the telemonitoring system. Interviews were recorded and analyzed thematically. Professionals involved in the implementation were sent an online questionnaire asking them about their perceptions of the service. RESULTS: We investigated the first 116 patients who used the service. Of these patients, 71 (61.2%) submitted data and the remainder (n=45, 38.8%) chose to self-monitor without electronic support. Of the 71 patients who submitted data, 35 (49%) received 152 alerts during their 2-week observation. A total of 67 red alerts were for oxygen saturation (SpO(2)) levels of ≤93%, and 15 red alerts were because patients recorded severe breathlessness. Out of 71 patients, 14 (20%) were admitted to hospital for an average stay of 3.6 (SD 4.5) days. Of the 45 who used written guidance alone, 7 (16%) were admitted to hospital for an average stay of 4.0 (SD 4.2) days and 1 (2%) died. Some patients who were advised to seek help did not do so, some because parameters improved on retesting and others because they felt no worse than before. All patients found self-monitoring to be reassuring. Of the 11 professionals who used the system, most found it to be useful and easy to use. Of these 11 professionals, 5 (45%) considered the system “very safe,” 3 (27%) thought it “could be safer,” and 3 (27%) wished to have more experience with it before deciding. In total, 2 (18%) felt that SpO(2) trigger thresholds were too high. CONCLUSIONS: Supported self-monitoring of patients with COVID-19 at home is reassuring to patients, is acceptable to clinicians, and can detect important signs of deterioration. Worryingly, some patients, because they felt well, occasionally ignored important signs of deterioration. It is important, therefore, to emphasize the importance of the early investigation and treatment of asymptomatic hypoxia at the time when patients are initiated and in the warning messages that are sent to patients

Strategies for Applying Electronic Health Records to Achieve Cost Saving Benefits

The American Recovery and Reinvestment Act (ARRA) of 2009 authorized the distribution of about $30 billion incentive funds to accelerate electronic health record (EHR) applications to improve the quality of care, safety, privacy, care coordination, and patients\u27 involvement in healthcare. EHR use has the potential of saving$731 in costs for hospitals per patient admission; however, most hospitals are not applying EHR to reach the level at which cost savings are possible. The purpose of this single case study was to explore strategies that IT leaders in hospitals can use to apply EHR to achieve the cost saving benefits. The participants were IT leaders and EHR super users at a large hospital in Texas with successful experience in applying EHR. Information systems success model formed the conceptual framework for the study. I conducted face-to-face interviews and analyzed organizational documents. I used qualitative textual data analysis method to identify themes. Five themes emerged from this study, which are ensuring information quality, ensuring system quality, assuring service quality, promoting usability, and maximizing net benefits of the EHR system. The findings of this study included four strategies to apply EHR; these strategies include engaging training staff, documenting accurately and in a timely manner, protecting patient data, and enforcing organizational best practice policies to maximize reimbursement and cost savings. The findings of this study could contribute to positive social change for the communities because EHR successful application includes lower cost for hospitals that may lead to the provision of affordable care to more low-income patients

Differences in Physician Use of Electronic Health Records: Development of a Scale Assessing Individual Factors Influencing Physician Actualization

Electronic health records (EHRs) are one of the most talked about topics within and surrounding health care organizations and the health care system in the United States; however, the U.S. has been slow to implement these computerized medical record systems into their organizations. One of the factors often overlooked regarding the implementation of EHRs, is the role of individual health care professionals and the effects produced by their interactions with the EHR as they perform their job duties throughout the day. Using a Theory of Organization-EHR Affordance Actualization as a guiding framework, the focus of this dissertation is to examine the factors that influence how physicians use the EHR at the individual-level during clinical interactions by analyzing physician perceptions of their interaction with the EHR while providing patient care in the exam room and how it influences their work process. A mixed methods approach was used to identify the affordances, EHR features, factors that influence EHR use, and individual physician characteristics that produce the visible effects of EHR use during the clinical encounter when individual physicians interact with the EHR. The findings of this study confirm the identification of individual level affordances proposed by Strong and colleagues and propose three additional affordances. This study also identified additional features that should be taken into consideration when investigating individual level affordance actualization. Finally, this study provides a survey tool for practice managers, health care executives, trainers, and vendors to use in order to better understand the individual user characteristics of their physicians, predict their patterns of use based on these user characteristics, and thus tailor their training to enhance affordance actualization and organizational goal attainment

COMBINING HUMAN FACTORS AND DATA SCIENCE METHODS TO EVALUATE THE USE OF FREE TEXT COMMUNICATION ORDERS IN ELECTRONIC HEALTH RECORDS

Medication errors are a leading cause of death in the United States. Electronic Health Records (EHR) along with Computerized Provider Order Entry (CPOE) are considered promising ways to reduce these errors. However, EHR systems have not eliminated medication errors. Moreover, in some cases they have facilitated errors due to issues such as poor usability and negative effects on clinical workflows. The use of unexpected free text within a CPOE system can serve as a marker that the system does not adequately support clinical workflow. Prior studies have looked at the use of free text within medication orders, but the inclusion of medication related information in communication for non-medication orders (CNMOs), a type of free text order, has not been adequately studied. This mixed-methods study identified the prevalence, nature and reasons for the inclusion of medication related information in CNMOs using a large sample of CNMOs placed at a mid-Atlantic hospital system in 2017, and via interviews with physicians. The study found that more than 42% of CNMOs contain medication related information. Moreover, the use of CNMOs varied significantly across provider types, hospital locations, patient settings and other factors. The study found 10 themes that might cause providers to adopt such workarounds, including missing functionality and poor usability. The viii study also identified several general challenges in communicating medication information in the EHR, and potential solutions to mitigate these challenges. This dissertation also demonstrates how natural language processing could be used to identify medication related CNMOs

The Electronic Health Record's Impact on Labor and Delivery Nurses' Cognitive Work

The Electronic Health Record’s Impact on Labor and Delivery Nurses’ Cognitive WorkAbstractBackground and objective: Despite recognition that electronic health record (EHR) use has introduced cognitive challenges for clinicians, few studies have evaluated its impact on the cognitive dimension of nurses’ work. Labor and delivery nurses may encounter unique challenges when using the electronic health record since they also interact with an electronic fetal monitoring system. This study sought to explore labor and delivery nurses’ perceptions of the EHR’s impact on their cognitive work with the goal of identifying patient safety implications. Methods and setting: This was a grounded theory study using dimensional and situational analysis. Data were interviews and observations with 21 labor nurses at two community hospitals in the Western United States. Results: The ways that nurses configured care when using the EHR varied across participants and sites and depended on how easily they integrated it into their practice. Individual, group, and situational factors facilitated or constrained integration. This took place in a dynamic, high-acuity, specialty clinical environment while using EHRs that were not designed for pregnant women. Nurses used clinical decision support and other cognitive support features that rarely worked as intended due to the lack of EHR customization to account for pregnancy physiology and unique risk factors in the perinatal patient. Nurses viewed the quality of their relationships with patients and their families as an integral part of caring for laboring women and felt that interaction with the EHR sometimes threatened this dimension of their work. Conclusions: When nurses were unable to integrate the EHR into care it resulted in numerous consequences that have important safety implications. Available cognitive support features lacked the specialty-specific support needed to care for laboring women and instead required nurses to track information in other ways that added to their cognitive burden and work routines. As a result, nurses and patients were not benefitting from the intended decision support and patient safety protections offered by appropriate risk assessment screens or critical alerts. These findings have important implications for the configuration and design of EHRs in perinatal settings