Online supplement for Health Information Exchange as a Multisided Platform: Adoption, Usage and Practice Involvement in Service Co- Production
|
|
- Brent Hawkins
- 5 years ago
- Views:
Transcription
1 Online supplement for Health Information Exchange as a Multisided Platform: Adoption, Usage and Practice Involvement in Service Co- Production A. Multisided HIE Platforms The value created by a HIE to members on any side is not only a function their own characteristics, but also depends on the members on other sides of the platform. Increase in the membership at each side can create positive or negative direct network effects among the members in the same side as well as indirect network effects among the members at the other sides. The direct effects are represented by the same-side externalities and the indirect effects by the cross-externalities. These effects are illustrated and denoted as positive or negative in Figure 1. We discuss the effects originating from these sides as follows. A.1. Patients The availability of the records to other users of an exchange is controlled by the informed consent of the patients (Goldstein 2010), and such consents are usually given with different levels of availability constraints. As the level and volume of patient consents increase, more data becomes available on the system. Hence, the sharing will be greater and the value of the HIE to its other participating user types will increase, leading to better service that patients receive from healthcare providers (Adler-Milstein et al. 2011). Furthermore, an increase in the level and volume of patient consents would increase the quality of healthcare services and reduce the probability of redundant tests. Both will eventually result in lower costs of healthcare services which payers including private insurance companies or state and governmental payers such as Medicare and Medicaid will benefit. On the other hand, although healthcare payers and providers will enjoy positive effects of indirect externalities from increased 1
2 number of patients with consent, the data providers such as laboratories and radiology centers will lose a part of their potential revenue by the decrease in the number of potential patients as the customers of their services. This happens due to the reduction in the number of redundant tests and increase in better care which also reduces the need for extra lab, radiology tests and other surplus clinical work. Finally, same-side direct network effects on the side of the patients are in general not significant. A.2. Healthcare Providers When more practices and physicians join a HIE and access medical data, the probability of receiving better care increases for patients. With a high number of physicians with access to previous medical records, patients will undergo fewer tests, receive more rapid healthcare service which in many emergency cases, may be vital for them. The better healthcare service and increased performance of healthcare providers will significantly lower the healthcare cost which benefits the payers. However, an increase in the number of physicians with access to previous medical records could also negatively affect the potential market share of laboratory and radiology centers in the same way that increased levels of patient consent do. The most interesting externality with this side is the direct network externality among physicians. When they become a member of HIE, the tests that they order will become available on the system and other physicians will be able to use them. In other words, the increased number of physician members will result in a richer medical dataset. For a detailed study of the network effects among physicians refer to (Yaraghi, et al. 2013a, 2013b). In conclusion, we can expect positive crossexternalities from the side of Healthcare Providers to the sides of the Patients and Payers, a potential negative effect on the side of Medical Data Providers, and positive same-side effects due to the reasons cited above. 2
3 A.3. Medical Data Providers As membership of medical data providers in a HIE increase, the chance of creating digital health records on the HIE platform also increase. This would positively affect both patients and healthcare providers. Patients would have a larger portion of their medical history online and thus will receive the benefits of HIE in increased healthcare quality and reduced costs at higher levels. In a similar way, with more data providers on the HIE system, healthcare providers can access larger pools of medical data of their patients and thus would be able to provide better care at lower costs. As discussed earlier, this would again benefit insurance companies and other payers by reducing the chances of paying for redundant tests. More importantly, the availability of more thorough and comprehensive medical histories reduces the chances of occurrences of unusual medical complications caused by wrong diagnoses and prescriptions. This would eventually reduce the healthcare costs for payers. When more data providers join a HIE and contribute to its digital database of medical records, less patients would need surplus tests and lab work. This happens due to the availability of previous medical records that reduces the chances of re-ordering redundant tests. Further, more comprehensive medical histories help physicians to make better decisions and provide better care which in turn would reduce the possibility of extra tests which would otherwise be administered based on wrong diagnoses and practices. Thus, the membership of more medical data providers in a HIE could create negative direct network externality among other data providers. In summary, we can expect positive cross-externalities from the side of Medical Data Providers to the sides of the Patients, Payers and Healthcare Providers, and a potential negative same-side effect due to the reasons cited above. A.4. Payers A significant value offered by a HIE to the participants on the Payers side is the capability it affords them to better control the quality of healthcare services and manage the billing and claims processes better 3
4 and smoother. The increase in membership on the Payers side increases the likelihood of better quality control over the healthcare services provided by medical providers which would result in better care for patients. It also enhances the precision and speed of coverage payments to medical providers as well as major data providers. A HIE provides a unique and rich pool of data which payers can utilize to better analyze the cost-effectiveness of their coverage policies and investigate the effects of many different options in healthcare coverage. As the number of members in the Payers side increases, their collective business intelligence leads to more sophisticated data analysis towards better coverage policies and healthcare services recommendations. In conclusion, we can expect positive cross-externalities from the side of Payers to the sides of the Patients, Healthcare Providers and Medical Data Providers and positive same-side effects due to the reasons cited above. As the time in which we collected the data, the practices could not push their medical data into the HIE system. All of the practices downloaded the data which is provided by labs, radiology centers and hospitals. Despite the fact that no direct exchange happened between the practices, they could access the data which others had previously ordered and was created by data providers on HIE system. As the number of member practices increases, the number of accessible medical documents on HIE system also increases. This is due to the fact that member practices encourage their patients to provide consent and allow their medical records to be shared with HIE members and thus the potential value of HIE for members increases. 4
5 Figure 1.Network externality effects among HIE members B. The HEALTHeLINK Platform HEALTHeLINK is the regional HIE that facilitates the electronic sharing of medical data among healthcare providers in Western New York using web portal technologies. The underlying HIE project began in 2004, led by the Buffalo Academy of Medicine. The project actively engaged Western New York physician community, SUNY at Buffalo, county and state public health departments, HealtheNet and UNYPHIED (Upstate New York Professional Healthcare Information & Education Demonstration Project), and was supported by a grant from the Community Health Foundation of Western and Central New York. HEALTHeLINK was created from these efforts in 2008 and has since been supported by funding from the Heal NY program of New York State. HEALTHeLINK is a collaborative effort among community healthcare providers, large hospital systems, major laboratories and radiology centers, and regional insurance providers. 5
6 Since its establishment in 2008, HEALTHeLINK has developed into a major four-sided platform as shown in Figure 1. Till recently, the exchange has attracted more than 2054 healthcare provider members within 430 practices. Healthcare professionals join HEALTHeLINK at the practice level. The medical data of over 500 thousand patients are available through HEALTHeLINK. All of the major hospitals, labs and radiology centers in Western New York have joined HEALTHeLINK and routinely push the data to the HEALTHeLINK database. Three insurance companies (payers) have joined HEALTHeLINK so far. HEALTHeLINK provides access to three types of patient medical records: Lab Reports, Radiology Reports and Hospital Transcriptions. Federal and state incentives cover the membership fees for practices so joining HEALTHeLINK is free for practices. When a patient visits a laboratory, radiology center or gets hospitalized, his medical records will be uploaded on a central data center managed by HEALTHeLINK. If the patient grants consent, then the participating practices will be able to view and download the patient s records through two different channels. The first channel is a fully automated channel which sends the digital data directly from labs, radiology centers and hospitals to the practices interoperable EMR systems. This is denoted as the Full-Service Channel. Practices will only receive the records of their own patients through this channel. The access to the records of the new patients is provided through the second channel: a web portal in which they have to manually search and download patient records. This is denoted as the Self-Service Channel. C. Data Processing and Analysis Procedure C.1. Degree Centrality Degree is the simplest yet the most appealing measure of in social network analysis (Ahuja et al. 2003). It reflects the number of other nodes that are directly connected to a particular node (Freeman 1979). Literature is abundant with evidence on the influence of social networks on innovation diffusion (Valente 1996, 2010, p. 14). Centrality is a measure of the prestige 6
7 and criticality associated with the position of a node in the network (Borgatti and Everett 2006) and is shown to be significant in influencing the behaviors of others in adopting new technologies and innovations (Carrington et al. 2005; Slater et al. 2007). Different metrics have been designed in the literature and each of these reflect different concepts with dissimilar interpretations (Freeman 1979). C.2. Betweenness Centrality Betweenness is the extent to which a node lies on the shortest paths between pairs of other nodes in the network (Freeman 1979). Nodes with high betweenness can influence the transmission of information among others by strategically withholding or distorting it (Shaw 1954). Social networks literature emphasizes the role of nodes with high betweenness in the maintenance of communication and their potential as key enablers of innovation diffusion (Grewal et al. 2006; Tucker 2008). Freeman (1979) introduced the simplest measure of betweenness. Consider a network of nodes. Assume that each link has a unit weight. Thus, the total weight of any path between a pair of nodes and is the number of links along this path. A shortest path between the pair nodes and is defined as a path with the minimum total path weight over all such paths connecting the pair in the network. Note that there could be several such shortest paths between nodes and. Let be the number of shortest paths between the pair. Let be the number of such shortest paths that contain a given node. The Freeman's (1979) measure of betweenness for node with respect to nodes and is. Despite its simplicity that has led to widespread use, Freeman s measure has two fundamental shortcomings. First, it does not take into account the fact that the weights on the links could vary in practical social networks since they represent the strengths of relationships between nodes. To overcome this, Brandes (2001) developed a new measure of betweenness where the 7
8 weights on the links are allowed to vary. This metric is more appropriate in networks where the link weights are of considerable importance in interpreting node relationships. The Brandes metric is computed similar to the Freeman metric, except that the total path weight is computed by adding the weights along a path. The details of this algorithm along with other alternative measures are discussed by Brandes (2008). Second, by adopting a constant unit weight for all links, the Freeman metric fixedly interprets paths with higher total path weights between a pair of nodes as weaker ties between them. However, in many social network contexts such as ours, higher total path weights could imply stronger ties. This is a clear limitation of the Freeman metric that is also efficiently overcome with the Brandes metric. In the current context of the network of common practitioners, we define the weight of a link as the inverse of the number of practitioners that are common to the two associated nodes. Hence, the paths with the minimum total weight represent the strongest ties between the two nodes. In this research, we employ the Brandes metric, computed by the Gephi software system (Bastian et al. 2009). We then used Gephi software (Bastian et al. 2009) to create two networks of common patients and common members and calculate the respective metrics. We used Gephi since it applies Brandes (2001) algorithm to calculate betweenness which as discussed in section 3.1 in the main paper is a much faster algorithm and also considers the weights of the links in calculating the betweenness. Both measures of are normalized so that they can be incorporated in a model together and the estimates of their coefficients be meaningfully interpreted. C.3. Service Value We merged the first two data sets described in the main paper, to create a panel data set of practices HIE access behavior. In this new data set, for each practice, we identify the number of access times to each medical record in each month through each channel. Monthly access to each of 8
9 the three different types of medical records (services) is considered as a proxy for the value of that specific service to each practice at the time. C.4. Urban/Rural Location The Population data set contains the population of 42 cities in which different practices are located in. The cities with a population of less than 17,000 are considered rural while others are considered urban. C.5. Market Share Market share of each practice is calculated based on the population of the city in which it is located in and the population of healthcare providers (physicians, nurses, etc) that practice in the same city. The market share of practice with a size of and a total healthcare providers population of members, in a city that has a total population of, is calculated as C.6. Tenure Tenure with HIE for each practice is calculated as the number of months since the adoption date until August C.7. Nurse Ratio Nurse ratio, is the ratio of nurses, nurse practitioners and physician assistants to specialists and primary care physicians in each practice. C.8. Isomorphic Quotients In this study, we define two forms of isomorphism: Patient-centric and Practitioner-centric. In patient-centric isomorphism, practices that share a large number of patients with other practices are considered as large, compared to the rest. In practitioner-centric isomorphism, practices that share a large number of practitioners with other practices qualify as large. The large practices are the most influential change agents in the local healthcare market, and the smaller ones tend to emulate their HIE adoption and usage behaviors. In general, large hospital systems and many well- 9
10 established large-sized practices usually satisfy both these criteria. However, some practices could also uniquely qualify as large under only one of these criteria. To calculate the physician and patient isomorphic quotients, we first rank practices by the number of physicians and patients that they share with the whole community. The practices in top 5% in the rankings of shared physicians and patients are considered as major practices. The ratio of physicians and patients that each smaller practice shares with these major practices is considered as its physician and patient dependency on major practices. Let denote the set of all the practices and hospital systems in a community. Let denote the set of practices where the number of patients shared by each practice with the rest in the community is more than a threshold value. The practices in the set are considered large by the patient criterion. Similarly, let denote the set of practices where the number of practitioners shared by each practice with the rest in the community is more than a threshold value. The practices in the set are considered large by the practitioner criterion. Consider a practice Let and denote the total number of patients that practice i shares with the entire market and the corresponding set of large practices, respectively. Then, the ratio { is a measure of the influence the set has over along the patient dimension. We term this ratio as the Patient-centric Isomorphic Quotient. Similarly, we define for any practice the quantities and as the total number of practitioners that shares with the entire market and the corresponding set of large practices, respectively. Then, the ratio is a measure of the influence the set has over along the practitioner dimension. We term this ratio as the Practitioner-centric Isomorphic Quotient. Both these quotients range between 0 and 1. Practices with larger values of these quotients are more likely to be influenced by the respective large practices in their HIE adoption and usage behaviors. 10
11 Figure 2 graphically represents the operationalization of each of the variables and their use in the respective analyses. Table 1 summarizes these six data sets. Data set name Full-service Self-service Demand Affiliation Adoption Population Description Logs of access through full-service channel to medical records Logs of access through self-service channel to medical records Logs of medical documents ordered by all practices, regardless of their membership status Access permissions of each practitioner at multiple practices Name, location and adoption date of member practices Population of cities in which member practices are located Table 1: Description of 6 data sets used in the empirical analysis Population dataset Adoption dataset Selfservice dataset Full service dataset Demand data set Affiliation dataset Market share Location Tenure, Tenure 2 Service value Patients network Members network Nurse ratio Degree Patient-centric isomorphism Physician-centric isomorphism Betweenness Usage Analysis by Eq. (1) Coproduction involvement Adoption Analysis by Eq. (2) Figure 2: The flowchart of variable operationalization 11
12 1. LogTCiVHR 2. LogTCiHUB Logtimetoadopt loglab 5. logradio logtrans 7. Tenure Tenure Rural 10. logmarketshare Nurse Degree Betweenness Practice efficiency Common patients with large practices 16.Common physicians with large practices Table 2: Correlation of the variables used in the empirical models
13 D. Conceptual Model Betweenness H2-1 Physician isomorphism H3-2 In-degree H1-1 Time to adopt H1-3 H3-1 Rural location Patient isomorphism Figure 3: Conceptual model of HIE adoption Tenure Betweenness H2-2 H2-3 Usage In-degree H1-2 H1-4 Rural location Figure 4: Conceptual model of HIE usage 13
14 Betweenness H2-4 Efficiency H2-5 Tenure Figure 5: Conceptual model of practice efficiency (co-production) in using HIE References Adler-Milstein, J., Bates, D. W., and Jha, A. K A survey of health information exchange organizations in the United States: implications for meaningful use. Annals of internal medicine 154(10) 666. Ahuja, M. K., Galletta, D. F., and Carley, K. M Individual and performance in virtual R&D groups: An empirical study. Management Science 49(1) Bastian, M., Heymann, S., and Jacomy, M Gephi: An open source software for exploring and manipulating networks. Borgatti, S. P., and Everett, M. G A graph-theoretic perspective on. Social networks 28(4) Brandes, U A faster algorithm for betweenness *. Journal of Mathematical Sociology 25(2) Brandes, U On variants of shortest-path betweenness and their generic computation. Social Networks 30(2) Carrington, P. J., Scott, J., and Wasserman, S Models and methods for innovation diffusion. Models and methods in social network analysis Freeman, L. C Centrality in social networks conceptual clarification. Social networks 1(3) Goldstein, M. M Health information technology and the idea of informed consent. The Journal of Law, Medicine & Ethics 38(1) Grewal, R., Lilien, G. L., and Mallapragada, G Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems. Management Science 52(7) Shaw, M. E Group structure and the behavior of individuals in small groups. The Journal of Psychology 38(1) Slater, M. D., Snyder, L. B., and Hayes, A. F communication network analysis. The Sage sourcebook of advanced data analysis methods for communication research Tucker, C Identifying Formal and Informal Influence in Technology Adoption with Network Externalities. Management Science 54(12)
15 Valente, T. W Network models of the diffusion of innovations. Computational & Mathematical Organization Theory 2(2) Valente, T. W Social Networks and Health: Models, Methods, and Applications: Models, Methods, and Applications, Oxford University Press, USA. Yaraghi, N., Du, A. Y., Sharman, R., Gopal, R. D., and Ramesh, R Network Effects in Health Information Exchange Growth. ACM Transactions on Management Information Systems (TMIS) 4(1) 1. Yaraghi, N., Du, A. Y., Sharman, R., Gopal, R. D., Ramesh, R., Singh, R., and Singh, G Professional and geographical network effects on healthcare information exchange growth: does proximity really matter? Journal of the American Medical Informatics Association 21(4)
Overview of the EHR Incentive Program Stage 2 Final Rule published August, 2012
I. Executive Summary and Overview (Pre-Publication Page 12) A. Executive Summary (Page 12) 1. Purpose of Regulatory Action (Page 12) a. Need for the Regulatory Action (Page 12) b. Legal Authority for the
More informationPULLING INFORMATION IN RESPONSE TO A PUSH: USAGE OF QUERY-BASED HEALTH INFORMATION EXCHANGE IN RESPONSE TO AN EVENT ALERT. PRELIMINARY REPORT
PULLING INFORMATION IN RESPONSE TO A PUSH: USAGE OF QUERY-BASED HEALTH INFORMATION EXCHANGE IN RESPONSE TO AN EVENT ALERT. PRELIMINARY REPORT Evidence from a study of three New York State Qualified Entities
More informationMeasures Reporting for Eligible Providers
Meaningful Use White Paper Series Paper no. 5a: Measures Reporting for Eligible Providers Published September 4, 2010 Measures Reporting for Eligible Providers The fourth paper in this series reviewed
More informationComparison of ACP Policy and IOM Report Graduate Medical Education That Meets the Nation's Health Needs
IOM Recommendation Recommendation 1: Maintain Medicare graduate medical education (GME) support at the current aggregate amount (i.e., the total of indirect medical education and direct graduate medical
More informationMinnesota Statewide Quality Reporting and Measurement System: Quality Incentive Payment System Framework
Minnesota Statewide Quality Reporting and Measurement System: Quality Incentive Payment System Framework AUGUST 2017 Minnesota Statewide Quality Reporting and Measurement System: Quality Incentive Payment
More informationWorking Paper Series
The Financial Benefits of Critical Access Hospital Conversion for FY 1999 and FY 2000 Converters Working Paper Series Jeffrey Stensland, Ph.D. Project HOPE (and currently MedPAC) Gestur Davidson, Ph.D.
More informationPaying for Outcomes not Performance
Paying for Outcomes not Performance 1 3M. All Rights Reserved. Norbert Goldfield, M.D. Medical Director 3M Health Information Systems, Inc. #Health Information Systems- Clinical Research Group Created
More informationBig Data Analysis for Resource-Constrained Surgical Scheduling
Paper 1682-2014 Big Data Analysis for Resource-Constrained Surgical Scheduling Elizabeth Rowse, Cardiff University; Paul Harper, Cardiff University ABSTRACT The scheduling of surgical operations in a hospital
More informationPublished in the Academy of Management Best Paper Proceedings (2004). VENTURE CAPITALISTS AND COOPERATIVE START-UP COMMERCIALIZATION STRATEGY
VENTURE CAPITALISTS AND COOPERATIVE START-UP COMMERCIALIZATION STRATEGY DAVID H. HSU The Wharton School, University of Pennsylvania 2000 Steinberg Hall Dietrich Hall, Philadelphia, PA 19104 INTRODUCTION
More informationREQUEST FOR PROPOSALS
REQUEST FOR PROPOSALS Improving the Treatment of Opioid Use Disorders The Laura and John Arnold Foundation s (LJAF) core objective is to address our nation s most pressing and persistent challenges using
More informationEssential Characteristics of an Electronic Prescription Writer*
Essential Characteristics of an Electronic Prescription Writer* Robert Keet, MD, FACP Healthcare practitioners have a professional mandate to prescribe the most appropriate and disease-specific medication
More informationQuality Improvement in the Advent of Population Health Management WHITE PAPER
Quality Improvement in the Advent of Population Health Management WHITE PAPER For healthcare organizations whose reimbursement and revenue are tied to patient outcomes, achieving performance on quality
More informationA strategy for building a value-based care program
3M Health Information Systems A strategy for building a value-based care program How data can help you shift to value from fee-for-service payment What is value-based care? Value-based care is any structure
More informationMidmark White Paper The Connected Point of Care Ecosystem: A Solid Foundation for Value-Based Care
Midmark White Paper The Connected Point of Care Ecosystem: A Solid Foundation for Value-Based Care Introduction This white paper examines how new technologies are creating a fully connected point of care
More informationInformation systems with electronic
Technology Innovations IT Sophistication and Quality Measures in Nursing Homes Gregory L. Alexander, PhD, RN; and Richard Madsen, PhD Abstract This study explores relationships between current levels of
More informationPROPOSED MEANINGFUL USE STAGE 2 REQUIREMENTS FOR ELIGIBLE PROVIDERS USING CERTIFIED EMR TECHNOLOGY
PROPOSED MEANINGFUL USE STAGE 2 REQUIREMENTS FOR ELIGIBLE PROVIDERS USING CERTIFIED EMR TECHNOLOGY On February 23, the Centers for Medicare & Medicaid Services (CMS) posted the much anticipated proposed
More informationFinding a Faster Path to Value-Based Care
Finding a Faster Path to Value-Based Care June 2016 Executive Summary The U.S. healthcare system is progressing along a continuum from volume- to valuebased care models where physicians and health systems
More informationThought Leadership Series White Paper The Journey to Population Health and Risk
AMGA Consulting Thought Leadership Series White Paper The Journey to Population Health and Risk The Journey to Population Health and Risk Howard B. Graman, M.D., FACP White Paper, January 2016 While the
More informationMedicaid and HIT: EHR s s for Medicaid Providers
Medicaid and HIT: EHR s s for Medicaid Providers National Medicaid Congress Christine H. Nye, Director Agency for Health Care Administration nyec@ahca.myflorida.com Better Health Care for All Floridians
More informationEvaluation at the Innovation Center
Evaluation at the Innovation Center William Shrank M.D. MSHS Director, Rapid Cycle Evaluation Group The Center for Medicare and Medicaid Innovation Centers for Medicare and Medicaid Services The Innovation
More informationJason C. Goldwater, MA, MPA Senior Director
The History of Health Information Technology in 45 Minutes Jason C. Goldwater, MA, MPA Senior Director April 5, 2017 Agenda Where We are With Health Information Technology and Where We are Going The Alphabet
More informationAN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE
AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE Yu-Li Huang, Ph.D. Assistant Professor Industrial Engineering Department New Mexico State University 575-646-2950 yhuang@nmsu.edu
More informationUsing Secondary Datasets for Research. Learning Objectives. What Do We Mean By Secondary Data?
Using Secondary Datasets for Research José J. Escarce January 26, 2015 Learning Objectives Understand what secondary datasets are and why they are useful for health services research Become familiar with
More informationHealth Information Technology
ACO Congress Oct 25, 2010 Los Angeles, CA Patient Centered Medical Home and Accountable Care Organizations Health Information Technology David K. Nace MD, Medical Director, McKesson Corporation Co-Chair,
More informationU.S. Healthcare Problem
U.S. Healthcare Problem U.S. Federal Spending GDP (%) Source: Congressional Budget Office This graph shows that government has to spend a lot of more money in healthcare in the future and it is growing
More informationPrepared for North Gunther Hospital Medicare ID August 06, 2012
Prepared for North Gunther Hospital Medicare ID 000001 August 06, 2012 TABLE OF CONTENTS Introduction: Benchmarking Your Hospital 3 Section 1: Hospital Operating Costs 5 Section 2: Margins 10 Section 3:
More informationEnvironmental Services: Delivering on the Patient-Centered Promise
Environmental Services: Delivering on the Patient-Centered Promise A patient s perception of hospital cleanliness is highly correlated with multiple safety, quality and experience measures. Executive Summary
More informationWelcome to the MS State Level Registry Companion Guide for
Welcome to the MS State Level Registry Companion Guide for Step 3 Attestation of your EHR This companion guide will assist providers as they move through the MS State Level Registry (MS SLR) online attestation
More informationCOLLABORATING FOR VALUE. A Winning Strategy for Health Plans and Providers in a Shared Risk Environment
COLLABORATING FOR VALUE A Winning Strategy for Health Plans and Providers in a Shared Risk Environment Collaborating for Value Executive Summary The shared-risk payment models central to health reform
More informationCreating a Patient-Centered Payment System to Support Higher-Quality, More Affordable Health Care. Harold D. Miller
Creating a Patient-Centered Payment System to Support Higher-Quality, More Affordable Health Care Harold D. Miller First Edition October 2017 CONTENTS EXECUTIVE SUMMARY... i I. THE QUEST TO PAY FOR VALUE
More informationHospital Readmissions
Hospital Readmissions The Long-Term Care Provider s Ultimate Survival Guide to Incorporating INTERACT TM Into Health Information Technology (HIT) In this survival guide, we ll give you the tips you need
More informationOverview of the EHR Incentive Program Stage 2 Final Rule
HIMSS applauds the Department of Health and Human Services for its diligence in writing this rule, particularly in light of the comments and recommendations made by our organization and other stakeholders.
More informationQuality Management Building Blocks
Quality Management Building Blocks Quality Management A way of doing business that ensures continuous improvement of products and services to achieve better performance. (General Definition) Quality Management
More informationAn EHR Overview for Pharma Marketers
An EHR Overview for Pharma Marketers April 2018 EHR Overview The Electronic Healthcare Record (EHR) is used by the provider and their staff to manage a broad range of patient care, such as administrative,
More informationTexas ACO invests in the Quanum portfolio to improve patient care
Case study: Premier Management Company North Texas Texas ACO invests in the Quanum portfolio to improve patient care Premier Management Company (PMC) manages 3 accountable care organizations (ACOs) in
More informationThe Connected Point of Care Ecosystem: A Solid Foundation for Value-Based Care
Includes Suggestions for Leveraging Improved BP Measurements to Achieve Quality Metrics Midmark White Paper The Connected Point of Care Ecosystem: A Solid Foundation for Value-Based Care Introduction This
More informationLEGISLATIVE REPORT NORTH CAROLINA HEALTH TRANSFORMATION CENTER (TRANSFORMATION INNOVATIONS CENTER) PROGRAM DESIGN AND BUDGET PROPOSAL
LEGISLATIVE REPORT NORTH CAROLINA HEALTH TRANSFORMATION CENTER (TRANSFORMATION INNOVATIONS CENTER) PROGRAM DESIGN AND BUDGET PROPOSAL SESSION LAW 2015-245, SECTION 8 FINAL REPORT State of North Carolina
More informationQUALITY PAYMENT PROGRAM
NOTICE OF PROPOSED RULE MAKING Medicare Access and CHIP Reauthorization Act of 2015 QUALITY PAYMENT PROGRAM Executive Summary On April 27, 2016, the Department of Health and Human Services issued a Notice
More informationAre physicians ready for macra/qpp?
Are physicians ready for macra/qpp? Results from a KPMG-AMA Survey kpmg.com ama-assn.org Contents Summary Executive Summary 2 Background and Survey Objectives 5 What is MACRA? 5 AMA and KPMG collaboration
More informationAppendix B: Formulae Used for Calculation of Hospital Performance Measures
Appendix B: Formulae Used for Calculation of Hospital Performance Measures ADJUSTMENTS Adjustment Factor Case Mix Adjustment Wage Index Adjustment Gross Patient Revenue / Gross Inpatient Acute Care Revenue
More informationBCBSM Physician Group Incentive Program
BCBSM Physician Group Incentive Program Organized Systems of Care Initiatives Interpretive Guidelines 2012-2013 V. 4.0 Blue Cross Blue Shield of Michigan is a nonprofit corporation and independent licensee
More informationSTAGE 2 PROPOSED REQUIREMENTS FOR MEETING MEANINGFUL USE OF EHRs 1
STAGE 2 PROPOSED REQUIREMENTS FOR MEETING MEANINGFUL USE OF EHRs 1 Requirement CPOE Use CPOE for medication orders directly entered by any licensed health care professional who can enter orders into the
More informationMACRA and MIPS. How Medicare Meaningful Use and PQRS are Changing
MACRA and MIPS How Medicare Meaningful Use and PQRS are Changing Link to recorded session: https://attendee.gotowebinar.com/recording/1305549490878052097 Presenting Today: Molly Goodhart Joined Quatris
More informationTechnology Fundamentals for Realizing ACO Success
Technology Fundamentals for Realizing ACO Success Introduction The accountable care organization (ACO) concept, an integral piece of the government s current health reform agenda, aims to create a health
More informationEffects of Physician Collaboration Network on Hospital Outcomes
Proceedings of the Fifth Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2012), Melbourne, Australia Effects of Physician Collaboration Network on Hospital Outcomes Shahadat
More information1. When will physicians who are not "meaningful" EHR users start to see a reduction in payments?
CPPM Chapter 7 Review Questions 1. When will physicians who are not "meaningful" EHR users start to see a reduction in payments? a. January 1, 2013 b. January 1, 2015 c. January 1, 2016 d. January 1, 2017
More informationMeaningful use care coordination criteria: Perceived barriers and benefits among primary care providers
Meaningful use care coordination criteria: Perceived barriers and benefits among primary care providers RECEIVED 10 June 2015 REVISED 18 August 2015 ACCEPTED 27 August 2015 PUBLISHED ONLINE FIRST 13 November
More informationYOUR HEALTH INFORMATION EXCHANGE
YOUR HEALTH INFORMATION EXCHANGE Introduction to Health Information Exchange Healthcare organizations are experiencing substantial pressures from initiatives and reforms such as new payment models, care
More informationHIE Implications in Meaningful Use Stage 1 Requirements
s in Meaningful Use Stage 1 Requirements HIMSS Health Information Exchange Steering Committee March 2010 2010 Healthcare Information and Management Systems Society (HIMSS). 1 An HIE Overview Health Information
More informationpaymentbasics Defining the inpatient acute care products Medicare buys Under the IPPS, Medicare sets perdischarge
Hospital ACUTE inpatient services system basics Revised: October 2007 This document does not reflect proposed legislation or regulatory actions. 601 New Jersey Ave., NW Suite 9000 Washington, DC 20001
More informationMedicare and Medicaid EHR Incentive Program. Stage 3 and Modifications to Meaningful Use in 2015 through 2017 Final Rule with Comment
Medicare and Medicaid EHR Incentive Program Stage 3 and Modifications to Meaningful Use in 2015 through 2017 Final Rule with Comment Measures, and Proposed Alternative Measures with Select Proposed 1 Protect
More informationOptumRx: Measuring the financial advantage
OptumRx: Measuring the financial advantage New study shows $11-16 PMPM medical savings when Optum care management and Optum pharmacy are provided together with medical benefits. Page 1 Synopsis Optum recently
More informationMaking the Business Case
Making the Business Case for Payment and Delivery Reform Harold D. Miller Center for Healthcare Quality and Payment Reform To learn more about RWJFsupported payment reform activities, visit RWJF s Payment
More informationpaymentbasics The IPPS payment rates are intended to cover the costs that reasonably efficient providers would incur in furnishing highquality
Hospital ACUTE inpatient services system basics Revised: October 2015 This document does not reflect proposed legislation or regulatory actions. 425 I Street, NW Suite 701 Washington, DC 20001 ph: 202-220-3700
More informationMeasures Reporting for Eligible Hospitals
Meaningful Use White Paper Series Paper no. 5b: Measures Reporting for Eligible Hospitals Published September 5, 2010 Measures Reporting for Eligible Hospitals The fourth paper in this series reviewed
More informationHow an ACO Provides and Arranges for the Best Patient Care Using Clinical and Operational Analytics
Success Story How an ACO Provides and Arranges for the Best Patient Care Using Clinical and Operational Analytics HEALTHCARE ORGANIZATION Accountable Care Organization (ACO) TOP RESULTS Clinical and operational
More informationOVERVIEW. Helping people live healthier lives and helping make the health system work better for everyone
OVERVIEW Helping people live healthier lives and helping make the health system work better for everyone About UnitedHealth Group UnitedHealth Group helps drive positive change in health care in the United
More informationRisk Adjustment Methods in Value-Based Reimbursement Strategies
Paper 10621-2016 Risk Adjustment Methods in Value-Based Reimbursement Strategies ABSTRACT Daryl Wansink, PhD, Conifer Health Solutions, Inc. With the move to value-based benefit and reimbursement models,
More informationFebruary 21, Regional Directors Child Nutrition Programs All Regions. State Agency Directors All States
United States Department of Agriculture Food and Nutrition Service 3101 Park Center Drive Alexandria, VA 22302-1500 SUBJECT: TO: February 21, 2003 Implementation of Interim Rule: Monitor Staffing Standards
More informationHow CME is Changing: The Influence of Population Health, MACRA, and MIPS
How CME is Changing: The Influence of Population Health, MACRA, and MIPS Table of Contents Population Health: Definition and Use Case The Future of Population Health and Performance Improvement MACRA and
More informationMedicare Quality Payment Program: Deep Dive FAQs for 2017 Performance Year Hospital-Employed Physicians
Medicare Quality Payment Program: Deep Dive FAQs for 2017 Performance Year Hospital-Employed Physicians This document supplements the AMA s MIPS Action Plan 10 Key Steps for 2017 and provides additional
More informationThe American Recovery and Reinvestment Act: Incentivizing Investments in Healthcare
The American Recovery and Reinvestment Act: Incentivizing Investments in Healthcare AT&T, Healthcare, and You Overview The American Recovery and Reinvestment Act of 2009 (ARRA) allocated more than $180
More informationAll ACO materials are available at What are my network and plan design options?
ACO Toolkit: A Roadmap for Employers What is an ACO? Is an ACO strategy right for my company? Which ACOs are ready? All ACO materials are available at www.businessgrouphealth.org What are my network and
More informationA Framework for Evaluating Electronic Health Records Overview - Applying to the Davies Ambulatory Awards Program Revised May 2012
A Framework for Evaluating Electronic Health Records Overview - Applying to the Davies Ambulatory Awards Program Revised May 2012 Introduction The Computer-Based Record Institute (CPRI) established the
More informationAre You Undermining Your Patient Experience Strategy?
An account based on survey findings and interviews with hospital workforce decision-makers Are You Undermining Your Patient Experience Strategy? Aligning Organizational Goals with Workforce Management
More informationHIE Implications in Meaningful Use Stage 1 Requirements
HIE Implications in Meaningful Use Stage 1 Requirements HIMSS 2010-2011 Health Information Exchange Committee November 2010 The inclusion of an organization name, product or service in this publication
More informationReport on the Pilot Survey on Obtaining Occupational Exposure Data in Interventional Cardiology
Report on the Pilot Survey on Obtaining Occupational Exposure Data in Interventional Cardiology Working Group on Interventional Cardiology (WGIC) Information System on Occupational Exposure in Medicine,
More informationThe attitude of nurses towards inpatient aggression in psychiatric care Jansen, Gradus
University of Groningen The attitude of nurses towards inpatient aggression in psychiatric care Jansen, Gradus IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you
More informationDefinition of Meaningful Use of Certified EHR Technology for Hospitals Approved by the HIMSS Board of Directors April 24, 2009
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 Definition of Meaningful Use of Certified EHR Technology for Hospitals Approved by
More informationNURSING RESEARCH (NURS 412) MODULE 1
KING SAUD UNIVERSITY COLLAGE OF NURSING NURSING ADMINISTRATION & EDUCATION DEPT. NURSING RESEARCH (NURS 412) MODULE 1 Developed and revised By Dr. Hanan A. Alkorashy halkorashy@ksu.edu.sa 1437 1438 1.
More informationBlue Care Network Physical & Occupational Therapy Utilization Management Guide
Blue Care Network Physical & Occupational Therapy Utilization Management Guide (Also applies to physical medicine services by chiropractors) January 2016 Table of Contents Program Overview... 1 Physical
More informationHow Your Hospital s Total Performance Score (TPS) Will Impact Your Medicare Payments
WHITE PAPER: How Your Hospital s Total Performance Score (TPS) Authors: Brooke Palkie, EdD, RHIA and David Marc, MBA, CHDA Copyright 2015 Panacea Healthcare Solutions, Inc. All Rights Reserved As a follow-up
More informationMeaningful Use Modified Stage 2 Roadmap Eligible Hospitals
Evident is dedicated to making your transition to Meaningful Use as seamless as possible. In an effort to assist our customers with implementation of the software conducive to meeting Meaningful Use requirements,
More informationIs there an impact of Health Information Technology on Delivery and Quality of Patient Care?
Is there an impact of Health Information Technology on Delivery and Quality of Patient Care? Amanda Hessels, PhD, MPH, RN, CIC, CPHQ Nurse Scientist Meridian Health, Ann May Center for Nursing 11.13.2014
More informationIncentives and Penalties
Incentives and Penalties CAUTI & Value Based Purchasing and Hospital Associated Conditions Penalties: How Your Hospital s CAUTI Rate Affects Payment Linda R. Greene, RN, MPS,CIC UR Highland Hospital Rochester,
More informationThe MIPS Survival Guide
The MIPS Survival Guide The Definitive Guide for Surviving the Merit-Based Incentive Payment System TABLE OF CONTENTS 1 An Introduction to the Merit-Based Incentive Payment System (MIPS) 2 Survival Tip
More informationSurveillance: Post-event Strategies
Surveillance: Post-event Strategies Developed by the Florida Center for Public Health Preparedness 1 Program Objectives Understand surveillance purpose and use in post-event epidemiologic investigation
More informationBrookings short ver. 1
The Brookings Institution The Potential of Medical Science The Practice of Medicine How to Close the Gap Remarks by James J. Mongan, MD December 15, 2006 I am here this morning to talk about the pressing
More informationACOs the Medicare Shared Savings Program And Other Healthcare Reform Payment Methods
A unique vision for an ever-changing healthcare environment ACOs the Medicare Shared Savings Program And Other Healthcare Reform Payment Methods Presented by Joe Laden, President, ORVA, LLC The Environment
More informationPublication Development Guide Patent Risk Assessment & Stratification
OVERVIEW ACLC s Mission: Accelerate the adoption of a range of accountable care delivery models throughout the country ACLC s Vision: Create a comprehensive list of competencies that a risk bearing entity
More informationHOT ISSUES FACING HOME HEALTH & HOSPICE AGENCIES. Luke James Chief Strategy Officer Encompass Home Health & Hospice
HOT ISSUES FACING HOME HEALTH & HOSPICE AGENCIES Luke James Chief Strategy Officer Encompass Home Health & Hospice Hospice Challenges Past & Present Face-to-Face (F2F) Implementation Sequestration Cuts
More informationBest Practices Contracting for Health IT Supporting Pay-for-Performance (P4P) Early Findings
Best Practices Contracting for Health IT Supporting Pay-for-Performance (P4P) Early Findings Researchers: Martin, Thomas R. PhD, Assistant Professor St. Joseph s University Department of Health Services;
More informationHealth Information Exchange 101. Your Introduction to HIE and It s Relevance to Senior Living
Health Information Exchange 101 Your Introduction to HIE and It s Relevance to Senior Living Objectives for Today Provide an introduction to Health Information Exchange Define a Health Information Exchange
More informationSpecial Open Door Forum Participation Instructions: Dial: Reference Conference ID#:
Page 1 Centers for Medicare & Medicaid Services Hospital Value-Based Purchasing Program Special Open Door Forum: FY 2013 Program Wednesday, July 27, 2011 1:00 p.m.-3:00 p.m. ET The Centers for Medicare
More informationAnalysis of 340B Disproportionate Share Hospital Services to Low- Income Patients
Analysis of 340B Disproportionate Share Hospital Services to Low- Income Patients March 12, 2018 Prepared for: 340B Health Prepared by: L&M Policy Research, LLC 1743 Connecticut Ave NW, Suite 200 Washington,
More informationSNOMED CT AND 3M HDD: THE SUCCESSFUL IMPLEMENTATION STRATEGY
SNOMED CT AND 3M HDD: THE SUCCESSFUL IMPLEMENTATION STRATEGY Federal Health Care Agencies Take the Lead The United States government has taken a leading role in the use of health information technologies
More informationAdopting Accountable Care An Implementation Guide for Physician Practices
Adopting Accountable Care An Implementation Guide for Physician Practices EXECUTIVE SUMMARY November 2014 A resource developed by the ACO Learning Network www.acolearningnetwork.org Executive Summary Our
More informationNonprofit partnership. A grass roots organization where Board of Directors have vested interest in its success.
1 Nonprofit partnership A grass roots organization where Board of Directors have vested interest in its success. The Board ensures representation from many of stakeholders throughout Ohio. 2 3 Federal
More informationClinical Operations. Kelvin A. Baggett, M.D., M.P.H., M.B.A. SVP, Clinical Operations & Chief Medical Officer December 10, 2012
Clinical Operations Kelvin A. Baggett, M.D., M.P.H., M.B.A. SVP, Clinical Operations & Chief Medical Officer December 10, 2012 Forward-looking Statements Certain statements contained in this presentation
More informationMeasuring the relationship between ICT use and income inequality in Chile
Measuring the relationship between ICT use and income inequality in Chile By Carolina Flores c.a.flores@mail.utexas.edu University of Texas Inequality Project Working Paper 26 October 26, 2003. Abstract:
More informationMACRA Quality Payment Program
The American College of Surgeons Resources for the New Medicare Physician System Table of Contents Understanding the... 3 Navigating MIPS in 2017... 4 MIPS Reporting: Individuals or Groups... 6 2017: The
More informationWhat are ACOs and how are they performing?
What are ACOs and how are they performing? What is an accountable care organisation (ACO)? ACOs involve groups of providers taking responsibility for all care for a given population within a capitated
More informationThe development of public eservices in Europe: New perspectives on public sector innovation
UNIVERSITÀ DEGLI STUDI DI URBINO "CARLO BO, Italy Department of Economics Society and Policy (DESP) The development of public eservices in Europe: New perspectives on public sector innovation Antonello
More informationThe Physician s Guide to Telemedicine in 2018
More Than A Great EHR The Physician s Guide to Telemedicine in 2018 The Physician s Guide to Adding Telemedicine to your Practice 2018 Bizmatics, Inc. Page 1 Table of Contents Introduction to Telemedicine...3
More informationUniversity Investments In the Library: What s the Payback? A Case Study at the University of Illinois at Urbana-Champaign
University Investments In the Library: What s the Payback? A Case Study at the University of Illinois at Urbana-Champaign The Need It used to be that the way you put together a library budget was to look
More informationQuestions and Answers
2018 Responsive Grants Program Questions and Answers Find information about the Responsive Grants Program at www.sierrahealth.org/rgp. FUNDING FOCUS... 2 WHAT SIERRA HEALTH FOUNDATION WILL FUND THROUGH
More informationPreparing for a New Era in Health Care
Preparing for a New Era in Health Care The Integrated Electronic Health Records System Presented by Ginger A. Baker, MS, MT (AAB) Objectives Build a foundation of understanding: The ARRA and HITECH Act
More informationHealth Management Information Systems: Computerized Provider Order Entry
Health Management Information Systems: Computerized Provider Order Entry Lecture 2 Audio Transcript Slide 1 Welcome to Health Management Information Systems: Computerized Provider Order Entry. The component,
More informationTransforming Health Care with Health IT
Transforming Health Care with Health IT Meaningful Use Stage 2 and Beyond Mat Kendall, Director of the Office of Provider Adoption Support (OPAS) March 19 th 2014 The Big Picture Better Healthcare Better
More information2011 Electronic Prescribing Incentive Program
2011 Electronic Prescribing Incentive Program Hardship Codes In 2012, the physician fee schedule amount for covered professional services furnished by an eligible professional who is not a successful electronic
More information