Assessment of Personal Health Care Management and Chronic Disease Prevalence: Comparative Analysis of Demographic, Socioeconomic, and Health-Related Variables.

BACKGROUND: The use of personal health care management (PHM) is increasing rapidly within the United States because of implementation of health technology across the health care continuum and increased regulatory requirements for health care providers and organizations promoting the use of PHM, particularly the use of text messaging (short message service), Web-based scheduling, and Web-based requests for prescription renewals. Limited research has been conducted comparing PHM use across groups based on chronic conditions. OBJECTIVE: This study aimed to describe the overall utilization of PHM and compare individual characteristics associated with PHM in groups with no reported chronic conditions, with 1 chronic condition, and with 2 or more such conditions. METHODS: Datasets drawn from the National Health Interview Survey were analyzed using multiple logistic regression to determine the level of PHM use in relation to demographic, socioeconomic, or health-related factors. Data from 47,814 individuals were analyzed using logistic regression. RESULTS: Approximately 12.19% (5737/47,814) of respondents reported using PHM, but higher rates of use were reported by individuals with higher levels of education and income. The overall rate of PHM remained stable between 2009 and 2014, despite increased focus on the promotion of patient engagement initiatives. Demographic factors predictive of PHM use included people who were younger, non-Hispanic, and who lived in the western region of the United States. There were also differences in PHM use based on socioeconomic factors. Respondents with college-level education were over 2.5 times more likely to use PHM than respondents without college-level education. Health-related factors were also predictive of PHM use. Individuals with health insurance and a usual place for health care were more likely to use PHM than individuals with no health insurance and no usual place for health care. Individuals reporting a single chronic condition or multiple chronic conditions reported slightly higher levels of PHM use than individuals reporting no chronic conditions. Individuals with no chronic conditions who did not experience barriers to accessing health care were more likely to use PHM than individuals with 1 or more chronic conditions. CONCLUSIONS: The findings of this study illustrated the disparities in PHM use based on the number of chronic conditions and that multiple factors influence the use of PHM, including economics and education. These findings provide evidence of the challenge associated with engaging patients using electronic health information as the health care industry continues to evolve.

The value of structured data elements from electronic health records for identifying subjects for primary care clinical trials.

BACKGROUND: An increasing number of clinical trials are conducted in primary care settings. Making better use of existing data in the electronic health records to identify eligible subjects can improve efficiency of such studies. Our study aims to quantify the proportion of eligibility criteria that can be addressed with data in electronic health records and to compare the content of eligibility criteria in primary care with previous work. METHODS: Eligibility criteria were extracted from primary care studies downloaded from the UK Clinical Research Network Study Portfolio. Criteria were broken into elemental statements. Two expert independent raters classified each statement based on whether or not structured data items in the electronic health record can be used to determine if the statement was true for a specific patient. Disagreements in classification were discussed until 100 % agreement was reached. Statements were also classified based on content and the percentages of each category were compared to two similar studies reported in the literature. RESULTS: Eligibility criteria were retrieved from 228 studies and decomposed into 2619 criteria elemental statements. 74 % of the criteria elemental statements were considered likely associated with structured data in an electronic health record. 79 % of the studies had at least 60 % of their criteria statements addressable with structured data likely to be present in an electronic health record. Based on clinical content, most frequent categories were: "disease, symptom, and sign", "therapy or surgery", and "medication" (36 %, 13 %, and 10 % of total criteria statements respectively). We also identified new criteria categories related to provider and caregiver attributes (2.6 % and 1 % of total criteria statements respectively). CONCLUSIONS: Electronic health records readily contain much of the data needed to assess patients' eligibility for clinical trials enrollment. Eligibility criteria content categories identified by our study can be incorporated as data elements in electronic health records to facilitate their integration with clinical trial management systems.

Extension of the primary care research object model (PCROM) as clinical research information model (CRIM) for the "learning healthcare system".

BACKGROUND: Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a "Learning Healthcare System" at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches. METHODS: Workflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions. RESULTS: The suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support. CONCLUSIONS: Research with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.

Effects of time constraints on clinician-computer interaction: a study on information synthesis from EHR clinical notes.

BACKGROUND: Time is a measurable and critical resource that affects the quality of services provided in clinical practice. There is limited insight into the effects of time restrictions on clinicians' cognitive processes with the electronic health record (EHR) in providing ambulatory care. OBJECTIVE: To understand the impact of time constraints on clinicians' synthesis of text-based EHR clinical notes. METHODS: We used an established clinician cognitive framework based on a think-aloud protocol. We studied interns' thought processes as they accomplished a set of four preformed ambulatory care clinical scenarios with and without time restrictions in a controlled setting. RESULTS: Interns most often synthesized details relevant to patients' problems and treatment, regardless of whether or not the time available for task performance was restricted. In contrast to previous findings, subsequent information commonly synthesized by clinicians related most commonly to the chronology of clinical events for the unrestricted time observations and to investigative procedures for the time-restricted sessions. There was no significant difference in the mean number of omission errors and incorrect deductions when interns synthesized the EHR clinical notes with and without time restrictions (3.5±0.5 vs. 2.3±0.5, p=0.14). CONCLUSION: Our results suggest that the incidence of errors during clinicians' synthesis of EHR clinical notes is not increased with modest time restrictions, possibly due to effective adjustments of information processing strategies learned from the usual time-constrained nature of patient visits. Further research is required to investigate the effects of similar or more extreme time variations on cognitive processes employed with different levels of expertise, specialty, and with different care settings.

Does initial length of stay impact 30-day readmission risk in pediatric asthma patients?

OBJECTIVES: Accountable care puts pressure on hospitals to manage care episodes. Initial length of stay (ILOS) and readmission risk are important elements of a care episode and measures of care quality. Understanding the association between these two measures can guide hospital efforts in managing care episodes. This study was designed to explore the association between ILOS and readmission risk in a cohort of pediatric asthma patients. MATERIALS AND METHODS: The sample cohort (n = 4965) consisted of all asthma patients discharged from Children's Hospitals and Clinics of Minnesota (CHC MN) from January 2008 through August 2012. Asthma discharges included cases with a principal diagnosis of asthma or certain respiratory cases with asthma listed as a secondary diagnosis. Multiple logistic regression was used to test associations, adjusting for covariates. RESULTS: Adjusting for covariates, we found no significant association between ILOS and readmission (OR: 1.04 [95% CI: 0.98-1.10]). Analyzing ILOS categorically by length of stay, one-day stays did not have a significantly higher readmission risk (OR:1.27 [95% CI: 0.87-1.85]) than two-day stays, which had the lowest observed readmission risk. Risk increased as ILOS exceeded two days but was not significantly different by day. We found no association when comparing the difference in actual versus expected ILOS and readmission risk (shorter than expected OR: 1.13 [95% CI: 0.74-1.71]; longer than expected OR: 0.97 [95% CI: 0.69-1.38]). CONCLUSIONS: Attempts to prolong ILOS would dramatically increase costs with little impact on readmissions. For example, increasing one-day visits to two-day visits would increase hospital patient days 38% (1870 d) in this cohort while decreasing total readmissions by 3.8% [95% CI: 3.6-4.0%]. Understanding the mechanisms that impact readmissions is essential in evaluating cost-effective approaches to improving patient outcomes and lowering the cost of care.

Telehealth: the promise of new care delivery models.

Telehealth possesses a significant potential to revolutionize healthcare delivery processes by challenging some of the long-held assumptions about healthcare delivery and by creating innovative alternative models. Those assumptions relate to the location-linked nature of healthcare and its episodic nature. Telehealth can challenge the assumption that healthcare is inextricably linked to the provider's location. Numerous models involving such approaches as interactive videoconferencing and store-and-forward technologies already exist. Telehealth also challenges the episodic nature of care. One example is provided by the models evolving from the convergence of three technologies: remote monitoring, electronic health records, and clinical decision support systems. Telehealth-based models of care can also lead to a reduced demand for services and greater efficiencies in the care process. These telehealth-enabled care delivery models have the potential to reduce the costs of care, improve quality, and mitigate provider shortages. However, the achievement of these goals is not straightforward. The current healthcare financing system is not designed to support such new models, and the existing healthcare culture is deeply ingrained within workflow processes and provider attitudes. A great deal of work remains to be done before the benefits of telehealth-based care delivery models are fully realized. Change is inherently risky but we must have the courage to assume the risk in order to create telehealth-driven innovations that lead to better and more cost-effective medical care for all.

A time-motion study to evaluate the impact of EMR and CPOE implementation on physician efficiency.

The objective of this research is to determine the impact of EMR and CPOE implementation on physician efficiency. A time series observational study was conducted within a hospital setting at six weeks pre-implementation, six weeks post-implementation and five months post-implementation. All 19 subjects were observed twice with one patient per observation. Physician follow-up rounding times per patient were measured. Physicians demonstrated a mean total rounding time of 18.79 minutes (pre-implementation); 16.97 minutes (six weeks post-implementation); and 12.97 minutes (five months post). Overall, the results showed a statistically significant F value = 8.26 > 1 (p = 0.0011) that signifies a reduction in physician rounding time within the hospital setting following EMR implementation. Results also showed overall standard deviations of 6.96 minutes (pre-implementation); 5.13 minutes (six weeks post); and 3.69 minutes (five months post), possibly signifying a reduction in variability and a narrower distribution of rounding times with increased similarity in physicians' rounding patterns.

Multiple Factors Drive Opioid Prescribing at the Time of Discharge.

Multiple factors potentially influence pain intensity or frequency, and consequently the need for an opioid prescription. This study aims to identify factors associated with being discharged with an outpatient opioid prescription. We constructed a database containing clinical, non-clinical, and organizational variables from the EHR that are potentially relevant for ordering an opioid at discharge. Descriptive statistics of these variables and univariate association analysis reveal that all of the examined variables to be statistically significantly associated with opioid prescription at discharge. Further, we fitted a random forest model to examine the information content in the examined variables regarding whether a patient will be discharged with an opioid. The model resulted in a mean AUC of 0.84, suggesting the factors examined in this study in combination contain significant information regarding prescription of an opioid at discharge.

Telehealth and the national health information technology strategic framework.

Telehealth has a role in the federally sponsored plan for health information technology (HIT) that encompasses electronic health records (EHRs) and the National Health Information Network (NHIN). The goals of telehealth and the national plan are complementary. One focuses on improving access to high quality health-care services and the other on the information systems to support those services. Telehealth needs the fully realized EHR to provide the best possible care when patients are geographically and chronologically separated from their providers. Some current telehealth projects are natural examples of how a distributed, accessible EHR such as that envisaged by the plan can be used to provide better care. The experiences of telehealth in organizing large networks of heterogeneous health-care entities can provide useful lessons as the process of implementing HIT moves forward.

Determinants of Consumer eHealth Information Seeking Behavior.

Patients are increasingly using the Internet and other technologies to engage in their own healthcare, but little research has focused on the determinants of consumer eHealth behaviors related to Internet use. This study uses data from 115,089 respondents to four years of the National Health Interview Series to identify the associations between one consumer eHealth behavior (information seeking) and demographics, health measures, and Personal Health Information Management (PHIM) (messaging, scheduling, refills, and chat). Individuals who use PHIM are 7.5 times more likely to search the internet for health related information. Just as health has social determinants, the results of this study indicate there are potential social determinants of consumer eHealth behaviors including personal demographics, health status, and healthcare access.

Using Publicly Available Data to Characterize Consumers Use of Email to Communicate with Healthcare Providers.

The use of patient focused technology has been proclaimed as a means to improve patient satisfaction and improve care outcomes. The Center for Medicaid/Medicare Services, through its EHR Incentive Program, has required eligible hospitals and professionals to send and receive secure messages from patients in order to receive financial incentives and avoid reimbursement penalties. Secure messaging between providers and patients has the potential to improve communication and care outcomes. The purpose of this study was to use National Health Interview Series (NHIS) data to identify the patient characteristics associated with communicating with healthcare providers via email. Individual patient characteristics were analyzed to determine the likelihood of emailing healthcare providers. The use of email for this purpose is associated with educational attainment, having a usual place of receiving healthcare, income, and geography. Publicly available data such as the NHIS may be used to better understand trends in adoption and use of consumer health information technologies.

The impact of electronic health records on people with diabetes in three different emergency departments.

OBJECTIVE: To evaluate if electronic health records (EHR) with prior clinical information have observable effects for patients with diabetes presenting to emergency departments (ED), we examined measures of quality and resource utilization. MATERIALS AND METHODS: Retrospective observational studies of patients in three ED (A=5510; B=4393; C=3324) were conducted comparing patients with prior information in the EHR to those without such information. Differences with respect to hospitalization, mortality, length of stay (LOS), and numbers of ED orders for tests, procedures and medications were examined after adjusting for age, gender, race, marital status, comorbidities and for acuity level within each ED. RESULTS: There were 7% fewer laboratory test orders at one ED and 3% fewer at another; fewer diagnostic procedures were performed at two of the sites. At one site 36% fewer medications were ordered. The odds of being hospitalized were lower for EHR patients at one site and hospital LOS was shorter at two of the sites. EHR patient ED LOS was 18% longer at one site. There was no demonstrable impact of an EHR on mortality. Results varied in magnitude and direction by site. DISCUSSION: The pattern of significant results varied by ED but tended to reveal reduced utilization and better outcomes for patients although EHR patients' ED LOS was longer at one site. CONCLUSIONS: The presence of prior information in an EHR may be a valuable adjunct in the care of diabetes patients in ED settings but the pattern of impact may vary from ED to ED.

Reuse of routinely collected health data for clinical research: considerations in a central England case study.

An increasing amount of electronic health data is being collected for patient care, and with it the opportunity to explore reusing this data, for example to support clinical research. We explore how researchers can be supported in identifying potential study participants using a semi-automated approach to query anonymised datasets remotely. This paper describes the socio-technical considerations when answering this question in a central England case study.

The use of count data models in biomedical informatics evaluation research.

OBJECTIVES: Studies on the impact and value of health information technology (HIT) have often focused on outcome measures that are counts of such things as hospital admissions or the number of laboratory tests per patient. These measures with their highly skewed distributions (high frequency of 0s and 1s) are more appropriately analyzed with count data models than the much more frequently used variations of ordinary least squares (OLS). Use of a statistical procedure that does not properly fit the distribution of the data can result in significant findings being overlooked. The objective of this paper is to encourage greater use of count data models by demonstrating their utility with an example based on the authors' current work. TARGET AUDIENCE: Researchers conducting impact and outcome studies related to HIT. SCOPE: We review and discuss count data models and illustrate their value in comparison to OLS using an example from a study of the impact of an electronic health record (EHR) on laboratory test orders. The best count data model reveals significant relationships that OLS does not detect. We conclude that comprehensive model checking is highly recommended to identify the most appropriate analytic model when the dependent variable being examined contains count data. This strategy can lead to more valid and precise findings in HIT evaluation studies.

Health insurance claim review using information technologies.

OBJECTIVES: The objective of this paper is to describe the Health Insurance Review and Assessment Service (HIRA)'s payment request (PARE) system that plays the role of the gateway for all health insurance claims submitted to HIRA, and the claim review support (CRS) system that supports the work of claim review experts in South Korea. METHODS: This study describes the two systems' information technology (IT) infrastructures, their roles, and quantitative analysis of their work performance. It also reports the impact of these systems on claims processing by analyzing the health insurance claim data submitted to HIRA from April 1 to June 30, 2011. RESULTS: The PARE system returned to healthcare providers 2.7% of all inpatient claims (97,930) and 0.1% of all outpatient claims (317,007) as un-reviewable claims. The return rate was the highest for the hospital group as 0.49% and the lowest rate was found in clinic group. The CRS system's detection rate of the claims with multiple errors in inpatient and outpatient areas was 23.1% and 2.9%, respectively. The highest rate of error detection occurred at guideline check-up stages in both inpatient and outpatient groups. CONCLUSIONS: The study found that HIRA's two IT systems had a critical role in reducing heavy administrative workloads through automatic data processing. Although the return rate of the problematic claims to providers and the error detection rate by two systems was low, the actual count of the returned claims was large. The role of IT will become increasingly important in reducing the workload of health insurance claims review.

The impact of electronic health records on care of heart failure patients in the emergency room.

OBJECTIVE: To evaluate if electronic health records (EHR) have observable effects on care outcomes, we examined quality and efficiency measures for patients presenting to emergency departments (ED). MATERIALS AND METHODS: We conducted a retrospective study of 5166 adults with heart failure in three metropolitan EDs. Patients were termed internal if prior information was in the EHR upon ED presentation, otherwise external. Associations of internality with hospitalization, mortality, length of stay (LOS), and numbers of tests, procedures, and medications ordered in the ED were examined after adjusting for age, gender, race, marital status, comorbidities and hospitalization as a proxy for acuity level where appropriate. RESULTS: At two EDs internals had lower odds of mortality if hospitalized (OR 0.55; 95% CI 0.38 to 0.81 and 0.45; 0.21 to 0.96), fewer laboratory tests during the ED visit (-4.6%; -8.9% to -0.1% and -14.0%; -19.5% to -8.1%) as well as fewer medications (-33.6%; -38.4% to -28.4% and -21.3%; -33.2% to -7.3%). At one of these two EDs, internals had lower odds of hospitalization (0.37; 0.22 to 0.60). At the third ED, internal patients only experienced a prolonged ED LOS (32.3%; 6.3% to 64.8%) but no other differences. There was no association with hospital LOS or number of procedures ordered. DISCUSSION: EHR availability was associated with salutary outcomes in two of three ED settings and prolongation of ED LOS at a third, but evidence was mixed and causality remains to be determined. CONCLUSIONS: An EHR may have the potential to be a valuable adjunct in the care of heart failure patients.

Cohort identification for clinical research: querying federated electronic healthcare records using controlled vocabularies and semantic types.

In the United Kingdom (UK), local initiatives have started to federate electronic healthcare records from different primary care clinical systems, mainly for the purposes of ensuring that health care services effectively meet the needs of the population. The use of such information is being investigated for clinical research, notably in patient cohort identification and recruitment. To achieve these aims, it is essential that the information from different systems can be searched from a single interface. While interoperability is a widely researched topic, interoperable methods and data sources in primary care are largely missing. This paper describes our approach to enabling primary care data in England to be searchable on a platform developed for performing large national collaborative primary care research studies throughout the United States.

Perception, satisfaction and utilization of the VALUE home telehealth service.

We conducted a randomized controlled trial to evaluate the perception, satisfaction and utilization of a home telehealth service for frail elderly people living independently in their home communities. Control group subjects continued with their usual care and intervention group subjects were able to supplement their usual care with the use of a web portal. The web portal allowed videoconferencing and electronic messaging between home care nurses and clients, ordering health-related and home care services, access to health-related information and general access to the Internet. A total of 99 eligible people (59 female, 40 male) from one urban and one rural study site agreed to participate in the study. Eighty-four subjects were active participants for nine months. There were no significant differences in perception of technology between the two groups at baseline. At 60-day follow-up, the intervention group was significantly more positive towards technology compared to their own baseline (P < 0.001) and compared to the 60-day scores for the controls (P < 0.001). The intervention group indicated that overall the telehealth service met their expectations (mean score 9 out of 10) and they would recommend it to others (mean score 9.5 out of 10). All subjects were able to use the portal without difficulty after brief instructions from the nurses. A total of 1054 videoconferences were conducted with the intervention subjects. Fifty-six of these (5%) had to be discontinued after successful connection because of technical problems. Intervention subjects made fewer emergency department visits than control subjects, more visits to the eye doctor, fewer visits in all categories of home care utilization, and lower use of transportation services. Frail elderly people are able to adopt home telehealth technologies which may enable them to maintain independent living arrangements.

Factors influencing health information technology adoption in Thailand's community health centers: applying the UTAUT model.

BACKGROUND: One of the most important factors for the success of health information technology (IT) implementation is users' acceptance and use of that technology. Thailand has implemented the national universal healthcare program and has been restructuring the country's health IT system to support it. However, there is no national data available regarding the acceptance and use of health IT in many healthcare facilities, including community health centers (CHCs). This study employed a modified Unified Theory of Acceptance and Use of Technology (UTAUT) structural model, to understand factors that influence health IT adoption in community health centers in Thailand and to validate this extant IT adoption model in a developing country health care context. METHODS: An observational research design was employed to study CHCs' IT adoption and use. A random sample of 1607 regionally stratified CHC's from a total of 9806 CHCs was selected. Data collection was conducted using a cross-sectional survey by means of self-administered questionnaire with an 82% response rate. The research model was applied using the partial least squares (PLS) path modeling. RESULTS: The data showed that people who worked in CHCs exhibited a high degree of IT acceptance and use. The research model analyses suggest that IT acceptance is influenced by performance expectancy, effort expectancy, social influence and voluntariness. Health IT use is predicted by previous IT experiences, intention to use the system, and facilitating conditions. CONCLUSIONS: Health IT is pervasive and well adopted by CHCs in Thailand. The study results have implications for both health IT developmental efforts in Thailand and health informatics research. This study validated the UTAUT model in the field context of a developing country's healthcare system and demonstrated that the PLS path modeling works well in a field study and in exploratory research with a complex model.

Impact of prior clinical information in an EHR on care outcomes of emergency patients.

A patient's prior clinical information available electronically can be helpful during the care process, particularly in the emergency department (ED). The effect of such information on quality and efficiency of ED patient care has not been adequately studied. This study uses secondary data to investigate its impact on surrogate measures of care quality and efficiency among 6,143 congestive heart failure, diabetic, and asthmatic patients in 3 EDs. Results show that in some subgroups of chronic patients in some EDs, availability of prior clinical information in the electronic health records was associated with significantly lower hospitalization rates, shorter inpatient length of stay, and reduction in the numbers of laboratory tests and diagnostic procedures ordered during the ED visit. However, there were also contradictory effects and lack of significance in other subgroups. The effects vary by ED and disease, highlighting the possibility of contextual differences influencing the effects of such clinical information.