Costs of using evidence-based implementation strategies for behavioral health integration in a large primary care system.

OBJECTIVE: To describe the cost of using evidence-based implementation strategies for sustained behavioral health integration (BHI) involving population-based screening, assessment, and identification at 25 primary care sites of Kaiser Permanente Washington (2015-2018). DATA SOURCES/STUDY SETTING: Project records, surveys, Bureau of Labor Statistics compensation data. STUDY DESIGN: Labor and nonlabor costs incurred by three implementation strategies: practice coaching, electronic health records clinical decision support, and performance feedback. DATA COLLECTION/EXTRACTION METHODS: Personnel time spent on these strategies was estimated for five broad roles: (a) project leaders and administrative support, (b) practice coaches, (c) clinical decision support programmers, (d) performance metric programmers, and (e) primary care local implementation team members. PRINCIPAL FINDING: Implementation involved 286 persons, 18 131 person-hours, costing $1 587 139 or $5 per primary care visit with screening or $38 per primary care visit identifying depression, suicidal thoughts and/or alcohol or substance use disorders, in a single year. The majority of person-hours was devoted to project leadership (35%) and practice coaches (34%), and 36% of costs were for the first three sites. CONCLUSIONS: When spread across patients screened in a single year, BHI implementation costs were well within the range for commonly used diagnostic assessments in primary care (eg, laboratory tests). This suggests that implementation costs alone should not be a substantial barrier to population-based BHI.

Clinical Decision Support for Recognizing and Managing Hypertensive Blood Pressure in Youth: No Significant Impact on Medical Costs.

OBJECTIVE: To evaluate economic costs from the health system perspective of an electronic health record-based clinical decision support (CDS) tool, TeenBP, designed to assist in the recognition and management of hypertension in youth. METHODS: Twenty primary care clinics within an integrated health system were randomized to the TeenBP CDS or usual care (UC), with patient enrollment from 4/15/14 to 4/14/16. The 12-month change in standardized medical care costs for insured patients aged 10 to 17 years without prior hypertension were calculated for each study arm. The primary analysis compared patients with ≥1 visit with blood pressure (BP) ≥95th percentile (isolated hypertensive BP), and secondary analyses compared patients with ≥3 visits within one year with BP ≥95th percentile (incident hypertension). Generalized estimating equation models estimated the difference-in-differences in costs between groups over time. RESULTS: Among 925 insured patients with an isolated hypertensive BP, the pre-to-post change in overall costs averaged $22 more for TeenBP CDS versus UC patients over 12 months, but this difference was not statistically significant (P = .723). Among 159 insured patients with incident hypertension, the pre-to-post change in overall costs over 12 months was higher by $227 per person on average for TeenBP CDS versus UC patients, but this difference also was not statistically significant (P = .313). CONCLUSIONS: The TeenBP CDS intervention was previously found to significantly improve identification and management of hypertensive BP in youth, and in this study, we find that this tool did not significantly increase care costs in its first 12 months of clinical use.

Design and implementation of an affordable, public sector electronic medical record in rural Nepal.

INTRODUCTION: Globally, electronic medical records are central to the infrastructure of modern healthcare systems. Yet the vast majority of electronic medical records have been designed for resource-rich environments and are not feasible in settings of poverty. Here we describe the design and implementation of an electronic medical record at a public sector district hospital in rural Nepal, and its subsequent expansion to an additional public sector facility.DevelopmentThe electronic medical record was designed to solve for the following elements of public sector healthcare delivery: 1) integration of the systems across inpatient, surgical, outpatient, emergency, laboratory, radiology, and pharmacy sites of care; 2) effective data extraction for impact evaluation and government regulation; 3) optimization for longitudinal care provision and patient tracking; and 4) effectiveness for quality improvement initiatives. APPLICATION: For these purposes, we adapted Bahmni, a product built with open-source components for patient tracking, clinical protocols, pharmacy, laboratory, imaging, financial management, and supply logistics. In close partnership with government officials, we deployed the system in February of 2015, added on additional functionality, and iteratively improved the system over the following year. This experience enabled us then to deploy the system at an additional district-level hospital in a different part of the country in under four weeks. We discuss the implementation challenges and the strategies we pursued to build an electronic medical record for the public sector in rural Nepal.DiscussionOver the course of 18 months, we were able to develop, deploy and iterate upon the electronic medical record, and then deploy the refined product at an additional facility within only four weeks. Our experience suggests the feasibility of an integrated electronic medical record for public sector care delivery even in settings of rural poverty.

How Appropriate Is All This Data Sharing? Building Consensus Around What We Need to Know About Shared Electronic Health Records in Extended Circles of Care.

BACKGROUND: The bulk of healthcare spending is on individuals who have complex needs related to age, income, chronic disease and mental illness. Care involves many different professions, and interoperable electronic health records (EHRs) are increasingly essential. OBJECTIVES: The objective of this paper is to describe the use of a nominal group technique (NGT) to develop a stakeholder-centred research agenda for clinical interoperability in extended circles of care that include social supports. METHODS: We held a day-long meeting with 30 stakeholders, including primary care providers, social supports, patient representatives, health region managers, technology experts, health organizations and experts in privacy, law and ethics. Participants considered, "What research needs to be done to better understand how EHRs should be shared across large healthcare teams that include social supports?" Following sensitizing presentations from researchers and participants, we used an NGT to generate and rank research questions on a 9-point Likert scale. We retained research questions that had a mean score of at least 6.5/9 by at least 70% of the participants over two rounds of consensus-building. RESULTS: Participants identified and ranked 57 research questions. Five items achieved consensus, related to 1) the impact of information sharing on care team outcomes, 2) data quality/accuracy, 3) cost/benefit, 4) what processes use what data and 5) regulation/legislation. CONCLUSION: Healthcare reforms are increasingly focused on systems that integrate and coordinate multidisciplinary care, facilitated by EHRs. Research prioritization will ensure common concerns and barriers are addressed and resolved.

Stage 1 of the meaningful use incentive program for electronic health records: a study of readiness for change in ambulatory practice settings in one integrated delivery system.

BACKGROUND: Meaningful Use (MU) provides financial incentives for electronic health record (EHR) implementation. EHR implementation holds promise for improving healthcare delivery, but also requires substantial changes for providers and staff. Establishing readiness for these changes may be important for realizing potential EHR benefits. Our study assesses whether provider/staff perceptions about the appropriateness of MU and their departments' ability to support MU-related changes are associated with their reported readiness for MU-related changes. METHODS: We surveyed providers and staff representing 47 ambulatory practices within an integrated delivery system. We assessed whether respondent's role and practice-setting type (primary versus specialty care) were associated with reported readiness for MU (i.e., willingness to change practice behavior and ability to document actions for MU) and hypothesized predictors of readiness (i.e., perceived appropriateness of MU and department support for MU). We then assessed associations between reported readiness and the hypothesized predictors of readiness. RESULTS: In total, 400 providers/staff responded (response rate approximately 25%). Individuals working in specialty settings were more likely to report that MU will divert attention from other patient-care priorities (12.6% vs. 4.4%, p = 0.019), as compared to those in primary-care settings. As compared to advanced-practice providers and nursing staff, physicians were less likely to have strong confidence in their department's ability to solve MU implementation problems (28.4% vs. 47.1% vs. 42.6%, p = 0.023) and to report strong willingness to change their work practices for MU (57.9% vs. 83.3% vs. 82.0%, p < 0.001). Finally, provider/staff perceptions about whether MU aligns with departmental goals (OR = 3.99, 95% confidence interval (CI) = 2.13 to 7.48); MU will divert attention from other patient-care priorities (OR = 2.26, 95% CI = 1.26 to 4.06); their department will support MU-related change efforts (OR = 3.99, 95% CI = 2.13 to 7.48); and their department will be able to solve MU implementation problems (OR = 2.26, 95% CI = 1.26 to 4.06) were associated with their willingness to change practice behavior for MU. CONCLUSIONS: Organizational leaders should gauge provider/staff perceptions about appropriateness and management support of MU-related change, as these perceptions might be related to subsequent implementation.

Impacts of EHR Certification and Meaningful Use Implementation on an Integrated Delivery Network.

Three years ago Intermountain Healthcare made the decision to participate in the Medicare and Medicaid Electronic Heath Record (EHR) Incentive Program which required that hospitals and providers use a certified EHR in a meaningful way. At that time, the barriers to enhance our home grown system, and change clinician workflows were numerous and large. This paper describes the time and effort required to enhance our legacy systems in order to pass certification, including filling 47 gaps in (EHR) functionality. We also describe the processes and resources that resulted in successful changes to many clinical workflows required by clinicians to meet meaningful use requirements. In 2011 we set meaningful use targets of 75% of employed physicians and 75% of our hospitals to meet Stage 1 of meaningful use by 2013. By the end of 2013, 87% of 696 employed eligible professionals and 100% of 22 Intermountain hospitals had successfully attested for Stage 1. This paper describes documented and perceived costs to Intermountain including time, effort, resources, postponement of other projects, as well as documented and perceived benefits of attainment of meaningful use.

Quality and cost improvement of healthcare via complementary measurement and diagnosis of patient general health outcome using electronic health record data: research rationale and design.

In this evolving 'third era of health', one of the US Health Care Reform Act's goals is to effectively facilitate the primary care physician's ability to better diagnose and manage the health outcome of the outpatient. That goal must include research on the complementary quantitative-qualitative assessment and rating of the patient's health status. This paper proposes an overview of the rationale and design of a research program for a balanced measurement and diagnostic clinical decision support system (CDSS) of the changing general health status of the patient -including disease- using electronic health record (EHR) data. The rationale, objectives, health metric-diagnostic tools architecture, simulation-optimization, and clinical trials are outlined. Resources, time frames, costs, feasibility, healthcare benefits and data-integration of the project are delineated. The basis and components of the research program to achieve an automated-CDSS to complement physician's clinical judgment, calculating a mathematical 'health equation' from each patient's EHR database, assisting physician-patient collaboration to diagnose, and improve general health outcomes is described. Use of multiple dimensional index, ways of classification, and causal factors' assessments, to arrive at the EHR-based CDSS algorithm-software providing a general health level and state rating of the patient are proposed. Its application could provide a compass for the general practitioner's best choice and use of the myriad of healthcare educational and technological options available with lower costs for everyday clinical practice and research. It could advance the approaches and focus of the 'eras of diseases', to the promising 'era of health', in an integrated, general approach to 'health.'

Are low income patients receiving the benefits of electronic health records? A statewide survey.

There are concerns that physicians serving low-income, Medicaid patients, in the United States are less likely to adopt electronic health records and, if so, that Medicaid patients will be denied the benefits from electronic health record use. This study seeks to determine whether physicians treating Medicaid patients were less likely to have adopted electronic health records. Physician surveys completed during physicians' license renewal process in Arizona were merged with the physician licensing data and Medicaid administrative claims data. Survey responses were received from 50.7 percent (6,780 out of 13,380) of all physicians practicing in Arizona. Physician survey responses were used to identify whether the physician used electronic health records and the degree to which the physician exchanged electronic health records with other health-care providers. Medicaid claims data were used to identify which physicians provided health care to Medicaid beneficiaries. The primary outcome of interest was whether Medicaid providers were more or less likely to have adopted electronic health records. Logistic regression analysis was used to estimate average marginal effects. In multivariate analysis, physicians with 20 or more Medicaid patients during the survey cycle were 4.1 percent more likely to use an electronic health record and 5.2 percent more likely to be able to transmit electronic health records to at least one health-care provider outside of their practice. These effects increase in magnitude when the analysis is restricted to solo practice physicians This is the first study to find a pro-Medicaid gap in electronic health record adoption suggesting that the low income patients served by Arizona's Health Care Cost Containment System are not at a disadvantage with regard to electronic health record access and that Arizona's model of promoting electronic health record adoption merits further study.

The future of monitoring in clinical research - a holistic approach: linking risk-based monitoring with quality management principles.

Since several years risk-based monitoring is the new "magic bullet" for improvement in clinical research. Lots of authors in clinical research ranging from industry and academia to authorities are keen on demonstrating better monitoring-efficiency by reducing monitoring visits, monitoring time on site, monitoring costs and so on, always arguing with the use of risk-based monitoring principles. Mostly forgotten is the fact, that the use of risk-based monitoring is only adequate if all mandatory prerequisites at site and for the monitor and the sponsor are fulfilled.Based on the relevant chapter in ICH GCP (International Conference on Harmonisation of technical requirements for registration of pharmaceuticals for human use - Good Clinical Practice) this publication takes a holistic approach by identifying and describing the requirements for future monitoring and the use of risk-based monitoring. As the authors are operational managers as well as QA (Quality Assurance) experts, both aspects are represented to come up with efficient and qualitative ways of future monitoring according to ICH GCP.

[OFEK virtual medical records: an evaluation of an integrated hospital-community system].

BACKGROUND: In 2005, an innovative system of hospital-community on-line medical records ("OFEK") was established at Clalit Health Services to reduce costs and improve medical care. GOALS: To examine the utilization of OFEK and its impact on quality indicators and medical-service utilization. METHOD: Examining frequency of use of OFEK with OFEK's own track-log data; "before" and "after" data were used to compare changes in quality indicators and service utilization for experimental versus control groups. RESULTS: Use of OFEK in primary-care clinics increased by hundreds of percent from 2005 to 2006 and continued rising in 2007 and 2008, albeit more slowly. At clinics in hospital catchment areas using OFEK extensively, the system reduced utilization of imaging services and, to a lesser extent laboratory use, and improved several quality measures. Analyses of the data from all catchment areas and from all study clinics revealed much weaker effects. In hospitals, the use of OFEK increased by tens of percent each year internal medicine wards showed a significant decrease in the number of laboratory tests and 3 CT tests compared with the control group. Wards using OFEK extensively showed a greater decrease in CT tests, in one imaging test, and in the average number of ambulatory hospitalizations. No similar changes were found in surgical wards. CONCLUSIONS: The introduction of OFEK affected some of the outcome measures examined. OFEK affects community clinics and hospital wards differently, with more consistent effects in the community. DISCUSSION AND SUMMARY: The study helps assess the extent to which OFEK's targets were achieved. In addition, it contributes to the development of measures to examine the impact of such systems, which can be used to assess a broad range of electronic-medical-information systems.