Effectiveness of clinical decision support in controlling inappropriate red blood cell and platelet transfusions, speciality specific responses and behavioural change.

BACKGROUND: Electronic clinical decision support (CDS) within Electronic Health Records has been used to improve patient safety, including reducing unnecessary blood product transfusions. We assessed the effectiveness of CDS in controlling inappropriate red blood cell (RBC) and platelet transfusion in a large acute hospital and how speciality specific behaviours changed in response. METHODS: We used segmented linear regression of interrupted time series models to analyse the instantaneous and long term effect of introducing blood product electronic warnings to prescribers. We studied the impact on transfusions for patients in critical care (CC), haematology/oncology (HO) and elsewhere. RESULTS: In non-CC or HO, there was significant and sustained decrease in the numbers of RBC transfusions after introduction of alerts. In CC the alerts reduced transfusions but this was not sustained, and in HO there was no impact on RBC transfusion. For platelet transfusions outside of CC and HO, the introduction of alerts stopped a rising trend of administration of platelets above recommended targets. In CC, alerts reduced platelet transfusions, but in HO alerts had little impact on clinician prescribing. CONCLUSION: The findings suggest that CDS can result in immediate change in user behaviour which is more obvious outside specialist settings of CC and HO. It is important that this is then sustained. In CC and HO, blood transfusion practices differ. CDS thus needs to take specific circumstances into account. In this case there are acceptable reasons to transfuse outside of these crude targets and CDS should take these into account.

Ethical Decision Making in Iot Data Driven Research: A Case Study of a Large-Scale Pilot.

IoT technologies generate intelligence and connectivity and develop knowledge to be used in the decision-making process. However, research that uses big data through global interconnected infrastructures, such as the 'Internet of Things' (IoT) for Active and Healthy Ageing (AHA), is fraught with several ethical concerns. A large-scale application of IoT operating in diverse piloting contexts and case studies needs to be orchestrated by a robust framework to guide ethical and sustainable decision making in respect to data management of AHA and IoT based solutions. The main objective of the current article is to present the successful completion of a collaborative multiscale research work, which addressed the complicated exercise of ethical decision making in IoT smart ecosystems for older adults. Our results reveal that among the strong enablers of the proposed ethical decision support model were the participatory and deliberative procedures complemented by a set of regulatory and non-regulatory tools to operationalize core ethical values such as transparency, trust, and fairness in real care settings for older adults and their caregivers.

Variation and Change Over Time in PROMIS-29 Survey Results Among Primary Care Patients With Type 2 Diabetes.

PURPOSE: We sought to describe results of patient-reported outcome measures implemented among primary care patients with diabetes and explore factors associated with changes in scores over time. METHODS: Two organizations serving diverse patient populations collected the PROMIS-29 survey at baseline and 3-month follow-up for patients with type 2 diabetes. Bayesian regression analysis was used to examine the relationship between patient characteristics and changes in PROMIS-29 scores. Exploratory analyses assessed relationships between goal-setting and changes in scores. RESULTS: The study population reported substantially more problems with physical functioning (mean: 42.5 at Site 1 and 38.9 at Site 2) and pain interference (mean: 58.0 at Site 1 and 61.1 at Site 2) compared to the general population (mean: 50; standard deviation: 10). At least 33% of patients had a clinically meaningful change (ie, at least half the standard deviation, or 5 points) in each PROMIS domain. For pain interference, 55% had no change, 22% improved by 5 or more points, and 23% worsened by 5 or more points. Bayesian regression analyses suggest that chronic conditions, insurance status, and Hispanic ethnicity are likely associated with decreased functioning over time. Exploratory analyses found that setting a mental health goal did not appear to be associated with improvement for anxiety or depression. CONCLUSIONS: Use of patient-reported outcome measures in routine clinical care identified areas of functional limitations among people with diabetes. However, changes in participants' PROMIS-29 scores over time were minimal. Research is needed to understand patterns of change in global and domain-specific functioning, particularly among racial/ethnic minorities.

Implementation of the PROMIS-29 in Routine Care for People With Diabetes: Challenges and Opportunities.

Using patient-reported outcome measures (PROMs) in care planning has the potential to improve care, but information about routine implementation in settings serving disadvantaged groups is needed. Two primary care clinics serving populations predominantly eligible for Medicaid and diverse in race/ethnicity implemented the PROMIS-29 as part of clinical care planning. Of the target population with diabetes, 26% (n = 490) completed the PROMs; the proportion that set a goal based on the PROMs differed by site. This report describes factors influencing the PROMs process and the results of interviews with patients and members of the care team about PROMs' implementation and impact.

Disparities in diabetes and hypertension care for individuals with serious mental illness.

OBJECTIVES: People with serious mental illnesses (SMI), including schizophrenia, bipolar disorder, and major depression, experience early mortality, partly due to comorbid physical health conditions such as diabetes and hypertension. This study examined the quality of diabetes and hypertension care for Medicaid and Medicare enrollees with SMI. STUDY DESIGN: We conducted a retrospective analysis of medical records and claims data from 3 health plans: a Medicaid plan for disabled adults, a Medicaid plan for low-income adults, and a Special Needs Plan for individuals dually enrolled in Medicaid and Medicare. The study population included 258 adults with SMI and diabetes and 241 adults with SMI and hypertension. METHODS: Existing quality measures for diabetes and hypertension from the Healthcare Effectiveness Data and Information Set (HEDIS) were adapted and applied to the SMI population for the 2012 calendar year. The rates of diabetes care and hypertension control for people with SMI were compared with national averages for Medicaid and Medicare managed care plans to examine disparities in care. RESULTS: Adults with SMI receive poor-quality care for diabetes and hypertension. Depending on the health plan, performance on the diabetes care and hypertension control HEDIS measures was 14 to 49 percentage points lower among the SMI population than the general Medicaid and Medicare populations. CONCLUSIONS: Findings highlight disparities in care for individuals with SMI compared with the general Medicaid and Medicare populations. Health plans demonstrated substantial room for improvement on almost all diabetes and hypertension HEDIS measures for the SMI population.

Is It Feasible to Use Electronic Health Records for Quality Measurement of Adolescent Care?

OBJECTIVE: To determine the extent to which it is feasible to implement quality measures on electronic health records (EHRs) as currently implemented in pediatric health centers. METHODS: A survey of information technology professionals at 10 institutions that provide primary care services to adolescents. The survey asked whether data about care was being captured electronically across the nine domains relevant to adolescent well care: Screening, Health Risks, Sexual Health, Diagnosis and History, Laboratory Results, Prescriptions, Referrals, Forms Management, and Patient Demographics. For each domain, we developed a scale of the extent to which the EHR makes quality measurement feasible. RESULTS: Overall feasibility scores varied across centers from 34% to 85% and from 53% to 80% across care domains. One centre reported 100% feasibility for 8 of 10 care domains. CONCLUSIONS: Electronic health records can facilitate quality improvement, but the feasibility of such use depends on the presence, validity, and accessibility of the quality data in the EHR. Even among the largest and most sophisticated pediatric EHR systems, quality of care measurement is not possible yet for all aspects of adolescent well care without manual effort to review and code data. Nevertheless, almost all quality measures were reported to be feasible in some systems.

Health IT-Enabled Care Coordination: A National Survey of Patient-Centered Medical Home Clinicians.

PURPOSE: Health information technology (IT) offers promising tools for improving care coordination. We assessed the feasibility and acceptability of 6 proposed care coordination objectives for stage 3 of the Centers for Medicare and Medicaid Services electronic health record incentive program (Meaningful Use) related to referrals, notification of care from other facilities, patient clinical summaries, and patient dashboards. METHODS: We surveyed physician-owned and hospital/health system-affiliated primary care practices that achieved patient-centered medical home recognition and participated in the Meaningful Use program, and community health clinics with patient-centered medical home recognition (most with certified electronic health record systems). The response rate was 35.1%. We ascertained whether practices had implemented proposed objectives and perceptions of their importance. We analyzed the association of organizational and contextual factors with self-reported use of health IT to support care coordination activities. RESULTS: Although 78% of the 350 respondents viewed timely notification of hospital discharges as very important, only 48.7% used health IT systems to accomplish this task. The activity most frequently supported by health IT was providing clinical summaries to patients, in 76.6% of practices; however, merely 47.7% considered this activity very important. Greater use of health IT to support care coordination activities was positively associated with the presence of a nonclinician responsible for care coordination and the practice's capacity for systematic change. CONCLUSIONS: Even among practices having a strong commitment to the medical home model, the use of health IT to support care coordination objectives is not consistent. Health IT capabilities are not currently aligned with clinicians' priorities. Many practices will need financial and technical assistance for health IT to enhance care coordination.

Self-management support activities in patient-centered medical home practices.

Innovation in primary care has increased interest in patient self-management techniques; little is known about the methods practices use to support self-management. This study is a survey of small practices, fewer than 5 physicians, with NCQA (National Committee for Quality Assurance) recognition (response rate 59.1%). Main measures include the number and delegation of self-management support activities. Practices reported a high proportion of self-management support activities. Physicians perform most of these activities. Practices that reported receiving training in self-management were more likely to have high self-management support to delegate. Self-management support activities are performed mainly by physicians. Practices that perform more of these activities have more nonindependent health care providers.

Mental health, substance abuse, and health behavior services in patient-centered medical homes.

PURPOSE: The purpose of this study was to understand mental health, substance use, and health behavior activities within primary care practices recognized by the National Committee for Quality Assurance as patient-centered medical homes (PCMHs). METHODS: We identified 447 practices with all levels of National Committee for Quality Assurance PCMH recognition as of March 1, 2010. We selected the largest practice from multisite groups, and 238 practices were contacted. We received 123 responses, for a 52% response rate. A 40-item web-based survey was collected. RESULTS: Of PCMH practices, 42% have a behavioral health clinician on site; social workers were the most frequent category of provider delivering behavioral services. There are also were care managers-distinct from behavioral health clinician-at 62% of practices. Surveyed practices were less likely to have procedures for referrals, communication, and patient scheduling for responding to mental health and substance use services than for other medical subspecialties (50% compared with 73% for cardiology and 69% for endocrinology). More than half of practices (62%) reported using electronic, standardized depression screening and monitoring; practices were less likely to screen for substance use than mental health. Among the practices, 54% used evidence-based health behavior protocols for mental health and substance use conditions. Practices reported that lack of reimbursement, time, and sufficient knowledge were obstacles. Practices serving a higher proportion of low-income patients performed more mental health organizational and clinical activities. CONCLUSIONS: In PCMHs, practice organization and response to behavioral issues seem to be less well developed than other types of medical care. These results support further efforts to develop whole-person care in the PCMH, with greater emphasis on access to and coordination of mental health, substance abuse, and health behavior services. Focusing primary care practices on this aspect of whole-person care will benefit from program sponsors' support and rewarding better integration with behavioral health.

Variations in measurement of sexual activity based on EHR definitions.

OBJECTIVE: The goal of this study was to compare the performance of 4 operational definitions of sexual activity by using data electronically abstracted from electronic health records (EHRs) and examine how documentation of Chlamydia screening and positivity vary according to definition of sexual activity. METHODS: Extracts were created from EHRs of adolescent females 12 to 19 years old who had ≥1 visit to a primary care practice during 2011 at 4 US pediatric health care organizations. We created 4 definitions of sexual activity derived from electronically abstracted indicator variables. Percent sexually active, documentation of Chlamydia screening, and rate of positive Chlamydia test results per 1000 adolescent females according to the sexual activity definition were calculated. RESULTS: The most commonly documented individual indicator of sexual activity was "patient report of being sexually active" (mean across 4 sites: 19.2%). The percentage of adolescent females classified as sexually active varied by site and increased as more indicator variables were included. As the definition of sexual activity expanded, the percentage of sexually active females who received at least 1 Chlamydia test decreased. Using a broader definition of sexual activity resulted in improved identification of adolescent females with Chlamydia infection. For each sexual activity definition and performance item, the difference was statistically significant (P < .0001). CONCLUSIONS: Information about sexual activity may be gathered from a variety of data sources, and changing the configurations of these indicators results in differences in the percentage of adolescent females classified as sexually active, screened for Chlamydia infection, and Chlamydia infection rates.

Using computer-extracted data from electronic health records to measure the quality of adolescent well-care.

OBJECTIVE: To determine whether quality measures based on computer-extracted EHR data can reproduce findings based on data manually extracted by reviewers. DATA SOURCES: We studied 12 measures of care indicated for adolescent well-care visits for 597 patients in three pediatric health systems. STUDY DESIGN: Observational study. DATA COLLECTION/EXTRACTION METHODS: Manual reviewers collected quality data from the EHR. Site personnel programmed their EHR systems to extract the same data from structured fields in the EHR according to national health IT standards. PRINCIPAL FINDINGS: Overall performance measured via computer-extracted data was 21.9 percent, compared with 53.2 percent for manual data. Agreement measures were high for immunizations. Otherwise, agreement between computer extraction and manual review was modest (Kappa = 0.36) because computer-extracted data frequently missed care events (sensitivity = 39.5 percent). Measure validity varied by health care domain and setting. A limitation of our findings is that we studied only three domains and three sites. CONCLUSIONS: The accuracy of computer-extracted EHR quality reporting depends on the use of structured data fields, with the highest agreement found for measures and in the setting that had the greatest concentration of structured fields. We need to improve documentation of care, data extraction, and adaptation of EHR systems to practice workflow.

There's more than one way to build a medical home.

OBJECTIVES: The patient-centered medical home (PCMH) is a critical aspect of delivery system reform. The purpose of this study was to examine variations in achievement of PCMH requirements across different types of practices. STUDY DESIGN: We used data on the points awarded, by standard and element, to 2369 practices recognized by September 2013 under the National Committee for Quality Assurance PCMH program, 2011 version. METHODS: We tested for differences across practice types in the percentage of practices achieving full credit for 27 element scores using likelihood ratio χ2 tests with an adjustment for multiple comparisons. RESULTS: Of the practices, 45% were affiliated with health systems, 22.6% were community health centers, and 5.3% were military treatment facilities. The remaining practices were physician-owned, 10% with at least 5 clinicians and 17.3% with less than 5. Even among Level 3 practices, there were significant differences across the practice types in the percentage of practices achieving full credit for 19 of 27 elements. Different types of practices demonstrated strengths in different medical home capabilities. CONCLUSIONS: Even among practices with the highest level of PCMH achievement, there are variations in key medical home capabilities. While research is needed to identify PCMH components having the greatest impact on outcomes, this research shows that the NCQA model is flexible enough to adapt to the strengths and needs of practices and the patients they serve. Efforts to support widespread dissemination of the PCMH model and practice transformation should recognize and build on these variations.

Support and strategies for change among small patient-centered medical home practices.

PURPOSE: We aimed to determine the motivations and barriers facing small practices that seek to adopt the patient-centered medical home (PCMH) model, as well as the type of help and strategies they use. METHODS: We surveyed lead physicians at practices with fewer than 5 physicians, stratified by state and level of National Committee for Quality Assurance PCMH recognition, using a Web-based survey with telephone, fax, and mail follow-up. The response rate was 59%, yielding a total sample of 249 practices from 23 states. RESULTS: Improving quality and patient experience were the strongest motivations for PCMH implementation; time and resources were the biggest barriers. Most practices participated in demonstration projects or received financial rewards for PCMH, and most received training or other kinds of help. Practices found training and help related to completing the PCMH application to be the most useful. Training for patients was both less common and less valued. The most commonly used strategies for practice transformation were staff training, systematizing processes of care, and quality measurement/goal setting. The least commonly endorsed strategy was involving patients in quality improvement. Practices with a higher level of PCMH recognition were more likely to have electronic health records, to report barriers, and to use measurement-based quality improvement strategies. CONCLUSIONS: To spread the adoption of the PCMH model among small practices, financial support, practical training, and other help are likely to continue to be important. Few practices involved patients in their implementation, so it would be helpful to test the impact of greater patient involvement in the PCMH.

Survey shows that fewer than a third of patient-centered medical home practices engage patients in quality improvement.

Directly involving patients and families in care improvement increasingly is viewed as an important component of patient-centered care. To assess the extent to which practices actually involve patients, we surveyed 112 patient-centered medical home practices in twenty-two states. Nearly all of these practices sought patient feedback. However, only 29 percent involved patients and families as advisers and sought feedback through surveys, and only 32 percent involved patients in a continuing role in quality improvement. Interviews showed that practices that highly value patient involvement overcame barriers to ongoing patient participation. We argue that a cultural shift is needed in how practices view patients as partners, not just in areas such as personal responsibility and self-management, but also in quality improvement and governance. Practices must gain more experience and see more examples of the benefits of engaging patients, and they may need more incentives and support for engaging them.

Consistency with the dietary approaches to stop hypertension diet among adults with diabetes.

Few studies have documented whether the dietary patterns of adults with diabetes are similar to the Dietary Approaches to Stop Hypertension (DASH) diet. Our objective was to determine differences in the degree of consistency with the DASH diet among adults with self-reported diabetes (with and without self-reported high blood pressure) compared with those without either disease. It was a cross-sectional study using data from 5,867 nonpregnant, noninstitutionalized adults aged ≥ 20 years with two reliable 24-hour recall dietary interviews in the National Health and Nutrition Examination Survey during 2003-2004 and 2005-2006. Diabetes and hypertension status were obtained from a questionnaire, and degree of consistency with the DASH diet was calculated based on nine nutrient targets (0- to 9-point DASH score). Multiple linear regression (adjusting for age, energy intake, and other covariates such as education, race, and body mass index) was performed to compare mean DASH scores and mean nutrient intakes among adults with diabetes, with and without high blood pressure, to those without either disease. No statistically significant differences were seen in mean DASH score among the three groups in the unadjusted or fully adjusted multivariable models. Compared with adults without either disease, those with only diabetes had higher intakes of fiber (8.1 g/1,000 kcal vs 7.6 g/1,000 kcal; P=0.02) and total fat as a percentage of total energy (35.3% vs 34.1%; P=0.006), and those with both diabetes and hypertension had higher sodium intake (153.0% of DASH target vs 146.6%; P=0.04). This information about individual nutrients could help guide the development of education programs.