Do Electronic Health Record Systems Increase Medicare Reimbursements? The Moderating Effect of the Recovery Audit Program

2021 ◽  
Author(s):  
Kartik K. Ganju ◽  
Hilal Atasoy ◽  
Paul A. Pavlou

Electronic health record (EHR) systems allow physicians to automate the process of entering patient data relative to manual entry in traditional paper-based records. However, such automated data entry can lead to increased reimbursement requests by hospitals from Medicare by overstating the complexity of patients. The EHR module that has been alleged to increase reimbursements is the Computerized Physician Order Entry (CPOE) system, which populates patient charts with default templates and allows physicians to copy and paste data from previous charts of the patient and other patients’ records. To combat increased reimbursements by hospitals from Medicare, the Centers for Medicare & Medicaid Services implemented the Recovery Audit Program first as a pilot in six states between 2005 and 2009 and then, nationwide in the entire United States in 2010. We examine whether the adoption of CPOE systems by hospitals is associated with an increase in reported patient complexity and if the Recovery Audit Program helped to attenuate this relationship. We find that the adoption of CPOE systems significantly increases patient complexity reported by hospitals, corresponding to an estimate of $1 billion increase in Medicare reimbursements per year. This increase was attenuated when hospitals were regulated by the Recovery Audit Program. Notably, those recovery auditors who developed the ability to identify the use of default templates, copied and pasted data, and cloned records were the most effective in reducing increased reimbursements. These findings have implications on how to combat Medicare reimbursements paid by taxpayer dollars with the Recovery Audit Program and how this information technology (IT) audit can prevent the misuse of information systems to create artificial business value of IT by hospitals. Contributions to information systems and healthcare research, practice, and public policy are discussed. This paper was accepted by Chris Forman, information systems.

2013 ◽  
Vol 04 (02) ◽  
pp. 293-303 ◽  
Author(s):  
L. Ozeran ◽  
C. Hamann ◽  
W. Bria ◽  
J. Shoolin

SummaryIn 2013, electronic documentation of clinical care stands at a crossroads. The benefits of creating digital notes are at risk of being overwhelmed by the inclusion of easily importable detail. Providers are the primary authors of encounters with patients. We must document clearly our understanding of patients and our communication with them and our colleagues. We want to document efficiently to meet without exceeding documentation guidelines. We copy and paste documentation, because it not only simplifies the documentation process generally, but also supports meeting coding and regulatory requirements specifically. Since the primary goal of our profession is to spend as much time as possible listening to, understanding and helping patients, clinicians need information technology to make electronic documentation easier, not harder. At the same time, there should be reasonable restrictions on the use of copy and paste to limit the growing challenge of ‘note bloat’. We must find the right balance between ease of use and thoughtless documentation. The guiding principles in this document may be used to launch an interdisciplinary dialogue that promotes useful and necessary documentation that best facilitates efficient information capture and effective display. Citation: Shoolin J, Ozeran L, Hamann C, Bria W. II. Association of Medical Directors of Information Systems Consensus on Inpatient Electronic Health Record Documentation. Appl Clin Inf 2013; 4: 293–303http://dx.doi.org/10.4338/ACI-2013-02-R-0012


2020 ◽  
Author(s):  
Philomena Njeri Ngugi ◽  
Ankica Babic ◽  
James Kariuki ◽  
Xenophon Santas ◽  
Violet Naanyu ◽  
...  

Abstract BackgroundElectronic Health Record Systems (EHRs) are being rolled out nationally in many low- and middle-income countries (LMICs) yet assessing actual system usage remains a challenge. We employed a nominal group technique (NGT) process to systematically develop high-quality indicators for evaluating actual usage of EHRs in LMICs.Methods An initial set of 14 candidate indicators were developed by the study team adapting the HIV Monitoring, Evaluation, and Reporting indicators format. A multidisciplinary team of 10 experts was convened in a two-day NGT workshop in Kenya to systematically evaluate, rate (using Specific, Measurable, Achievable, Relevant, and Time-Bound (SMART) criteria), prioritize, refine, and identify new indicators. NGT steps included introduction to candidate indicators, silent indicator ranking, round-robin indicator rating, and silent generation of new indicators. Results: Candidate indicators were rated highly on SMART criteria (4.05/5). NGT participants settled on 15 final indicators, categorized as system use (4); data quality (3), system interoperability (3), and reporting (5). Data entry statistics, systems uptime, and EHRs variable concordance indicators were rated highest. ConclusionThis study describes a systematic approach to develop and validate quality indicators for determining EHRs use and provides LMICs with a multidimensional tool for assessing success of EHRs implementations.


2020 ◽  
Vol 27 (9) ◽  
pp. 1401-1410
Author(s):  
Ross W Hilliard ◽  
Jacqueline Haskell ◽  
Rebekah L Gardner

Abstract Objective The study sought to examine the association between clinician burnout and measures of electronic health record (EHR) workload and efficiency, using vendor-derived EHR action log data. Materials and Methods We combined data from a statewide clinician survey on burnout with Epic EHR data from the ambulatory sites of 2 large health systems; the combined dataset included 422 clinicians. We examined whether specific EHR workload and efficiency measures were independently associated with burnout symptoms, using multivariable logistic regression and controlling for clinician characteristics. Results Clinicians with the highest volume of patient call messages had almost 4 times the odds of burnout compared with clinicians with the fewest (adjusted odds ratio, 3.81; 95% confidence interval, 1.44-10.14; P = .007). No other workload measures were significantly associated with burnout. No efficiency variables were significantly associated with burnout in the main analysis; however, in a subset of clinicians for whom note entry data were available, clinicians in the top quartile of copy and paste use were significantly less likely to report burnout, with an adjusted odds ratio of 0.22 (95% confidence interval, 0.05-0.93; P = .039). Discussion High volumes of patient call messages were significantly associated with clinician burnout, even when accounting for other measures of workload and efficiency. In the EHR, “patient calls” encompass many of the inbox tasks occurring outside of face-to-face visits and likely represent an important target for improving clinician well-being. Conclusions Our results suggest that increased workload is associated with burnout and that EHR efficiency tools are not likely to reduce burnout symptoms, with the exception of copy and paste.


2007 ◽  
Vol 15 (3) ◽  
pp. 187-192
Author(s):  
Milica Katić ◽  
Dragan Soldo ◽  
Zlata Ozvačić ◽  
Sanja Blažeković-Milaković ◽  
Mladenka Vrcić-Keglević ◽  
...  

2020 ◽  
Vol 27 (11) ◽  
pp. 1648-1657
Author(s):  
Tiago K Colicchio ◽  
Pavithra I Dissanayake ◽  
James J Cimino

Abstract Objective To develop a collection of concept-relationship-concept tuples to formally represent patients’ care context data to inform electronic health record (EHR) development. Materials and Methods We reviewed semantic relationships reported in the literature and developed a manual annotation schema. We used the initial schema to annotate sentences extracted from narrative note sections of cardiology, urology, and ear, nose, and throat (ENT) notes. We audio recorded ENT visits and annotated their parsed transcripts. We combined the results of each annotation into a consolidated set of concept-relationship-concept tuples. We then compared the tuples used within and across the multiple data sources. Results We annotated a total of 626 sentences. Starting with 8 relationships from the literature, we annotated 182 sentences from 8 inpatient consult notes (initial set of tuples = 43). Next, we annotated 232 sentences from 10 outpatient visit notes (enhanced set of tuples = 75). Then, we annotated 212 sentences from transcripts of 5 outpatient visits (final set of tuples = 82). The tuples from the visit transcripts covered 103 (74%) concepts documented in the notes of their respective visits. There were 20 (24%) tuples used across all data sources, 10 (12%) used only in inpatient notes, 15 (18%) used only in visit notes, and 7 (9%) used only in the visit transcripts. Conclusions We produced a robust set of 82 tuples useful to represent patients’ care context data. We propose several applications of our tuples to improve EHR navigation, data entry, learning health systems, and decision support.


2019 ◽  
Vol 26 (1) ◽  
pp. 592-612 ◽  
Author(s):  
Angeline Kuek ◽  
Sharon Hakkennes

This study aimed to assess the digital literacy levels and attitudes towards information systems of staff in a health service that will be implementing an electronic health record so that barriers towards implementation could be addressed. A survey measuring staff confidence levels and their attitudes towards information systems was developed. Data were collected over a five-week period, with data analysed using frequency analysis and a chi-square analysis. There were 407 respondents to the survey. The majority (70-80%) of which reported high digital literacy levels, expressing confidence in using technology. Respondents also reported positive attitudes towards information systems. However, one-fifth reported anxiety using information systems. Given poor staff engagement with information systems adversely affects the safety and quality of patient care, health services should provide targeted education and training to address staff with low digital literacy levels and/or confidence with using information systems prior to implementation of an electronic health record system.


2020 ◽  
Vol 29 (01) ◽  
pp. 167-168

Burek P, Scherf N, Herre H. Ontology patterns for the representation of quality changes of cells in time. J Biomed Semantics 2019;10(1):16 https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-019-0206-4 Denaxas S, Gonzalez-Izquierdo A, Direk K, Fitzpatrick NK Fatemifar G, Banerjee A, Dobson RJB, Howe LJ, Kuan V, Lumbers RT, Pasea L, Patel RS, Shah AD, Hingorani AD, Sudlow C, Hemingway H. UK phenomics platform for developing and validating electronic health record phenotypes: CALIBER. J Am Med Inform Assoc 2019;26(12):1545-59 https://academic.oup.com/jamia/article/26/12/1545/5536916 Rector A, Schulz S, Rodrigues J-M, Chute CG, Solbrig H. On beyond Gruber: “Ontologies” in today's biomedical information systems and the limits of OWL. J Biomed Inform: X 2019 Jun 1;2:100002 https://academic.oup.com/jamia/article/26/12/1545/5536916 Shen F, Zhao Y, Wang L, Mojarad MR, Wang Y, Liu S, Liu H. Rare disease knowledge enrichment through a data-driven approach. BMC Med Inform Decis Mak 2019;19(1):32 https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-019-0752-9


2021 ◽  
Vol 10 (1) ◽  
pp. 97
Author(s):  
Reza Abbasi ◽  
Reza Khajouei ◽  
Monireh Sadeghi Jabali ◽  
Moghadameh Mirzaei

Introduction: One of the well-known problems related to the information quality is the information incompleteness in health information systems. The purpose of this study was to investigate the completeness rate of patients’ information recorded in the hospital information system, sending information from which to Iranian electronic health record system (SEPAS) seemed to be unsuccessful.Methods: This study was conducted in six hospitals associated with Kerman University of Medical Sciences (KUMS) in Iran. In this study, 882 records which had failed to be sent from three hospital information systems to SEPAS were reviewed and the data were collected using a checklist. Data were analyzed using the descriptive and inferential statistics with SPSS.18.Results: A total of 18758 demographic and clinical information elements were examined. The rate of completeness was 55%. The highest completeness rate of demographic information was related to name, surname, gender, nationality, date of birth, father's name, marital status, place of residence, telephone number (79-100%), and in clinical information it was related to the final diagnosis (74%). The completeness rate of some information elements was significantly different among the hospitals (p <0.05). The completeness rate of information communicated to the Iranian national electronic health record was at a moderate level.Conclusion: This study showed that completeness rate is different among hospitals using the same hospital information system. The results of this study can help the health policymakers and developers of the national electronic health record in developing countries to improve completeness rate and also information quality in health information systems.


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