Electronic Health Records in MPL - PIAA

APRIL 2016

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Special Feature: Part 2 of 2

How ONC’s SAFER Guides can help improve your EHR

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Electronic Health Records in MPL lectronic health records (EHRs) increasingly have replaced paper and checkbox forms in physicians’ offices, clinics, and health systems and the number of providers using EHR and computerized provider order entry (CPOE) increases daily. However, building an EHR system is a complex undertaking. As systems have been adopted and continue to evolve, medical professional liability (MPL) claims linked to EHR use have arisen.1, 2

CMS to phase out ‘meaningful use’ Case Studies in EHR

80% 70%

Figure 1: Allegation Trends Noted by PIAA Member Companies 71%

60%

52%

50% 40%

24%

30% 20%

19%

10% 0% Copy-and-paste practices

Failure to review all Breach of system Insufficient provider available EHR data training

Source: PIAA 2012 EHR Survey

1 Joint Commission. 2015 March 30. Investigations of Health IT-related Deaths, Serious Injuries or Unsafe Conditions Final Report; [accessed 2015 Oct 3] https://www.healthit.gov/sites/default/files/safer/pdfs/Investigations_HealthIT_related_SE_ Report_033015.pdf 2 Fleeter, T. 2012 Aug. Potential Liability Risks of Electronic Health Records. American Academy of Orthopaedic Surgeons; [accessed 2015 Dec 9] http://www.aaos.org/news/aaosnow/aug12/managing9.asp

This Research Notes discusses EHR issues brought to light by a PIAA survey on EHRs and illustrates how the ONC SAFER Guides could be used to identify and correct those issues. It also presents EHR-related MPL case studies. A previous issue of Research Notes (Part 1) summarized responses to the 2012 PIAA claims and risk management survey that asked MPL insurers to identify EHR issues. They were asked questions about allegation trends linked to the use of EHRs, which EHR functions heighten claim risks and what expectations providers and MPL insurers have for maintaining and enhancing EHR systems, among others.3, 4 More than half (53%) of respondents to PIAA’s EHR Survey said they had seen EHR-related MPL (formerly medical malpractice) claims. Top allegation trends identified by the respondents included copyand-paste practices, failure to 3 PIAA internal document. 2012 Jan. PIAA 2012 EHR Survey. PIAA’s Claims and Risk Management Section members conducted a survey completed by 43 member PIAA Medical Professional Liability Insurance Companies. The survey goal was to measure the exposure of EHRs, the impact on allocated loss adjustment expenses, ways to prevent pitfalls, and best practices to educate stakeholders. Respondents were offered 29 questions covering claims, patient safety and risk management. 4 PIAA Research Notes. 2015 Jan. Electronic Health Records and a Summary Analysis of the 2012 PIAA EHR Survey. Proprietary PIAA member publication.

Figure 2: ONC SAFER Guides for EHRs Foundational

High-Priority Practices Guide–Allows the determination of “highrisk” and “high-priority” aspects of the EHR system and its use. This guide helps organizations assess where they should concentrate their EHR safety improvement efforts.

Organizational Responsibilities Guide—Assesses tasks, processes, and activities that users and developers must carry out to ensure safe and effective EHR implementation and use.

Computing Infrastructure Contingency Planning Guide—Focuses on preparations that should be complete before the EHR experiences a hardware, software, or power failure.

System Configuration Guide—Guides analysis of the physical environment in which the EHR will operate, as well as the infrastructure required to run the EHR.

System Interfaces Guide— Recommends processes that enable the physical and logical connection of different hardware devices and software so they can share information.

Source: DHHS Office of the National Coordinator for Health Information Technology, Safety Assurance Factors for EHR Resilience Guides for EHRs

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Clinically Focused Patient Identification Guide—Guides methods for creating new patient records in the EHR and patient registration and retrieval of information on existing patients.

Computerized provider Order Entry with Decision Support Guide—Emphasizes what is required for safe electronic ordering of medications and diagnostic tests and point-of-care clinical decision support.

Test Results Reporting and Follow-up Guide— Assesses the delivery of test results to the appropriate providers.

Clinician Communication Guide—Shows what is needed for successful consultations or referrals, discharge-related communications, and patient-related messaging between clinicians.

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review all data available in the record, and breach of the systems by users (Figure 1). Recent studies have identified adverse patient events increasing in number as providers instituted the extensive changes required to turn from paper to electronic charts. A recent report issued by the Joint Commission found 3.5% (120) of 3,375 sentinel events resulting in permanent patient harm or death had health IT-related contributing factors (Joint Commission, 2015). Even though there continues to be controversy over the safe use of EHRs, the electronic patient record is here to stay. Adoption of technology across all industries with the goal of increasing productivity and curtailing costs is a major impetus for providers to adopt more advanced healthcare information technologies (health IT). The federal government’s requirement that healthcare providers develop EHRs is based in part on the position that, ultimately, EHRs are expected to result in safer and higher quality patient care. Studies to date offer mixed findings. As part of its push to shift physician payment from a volume-based system to one based on value, the Department of Health and Human Services (DHHS) Centers for Medicare and Medicaid Services (CMS) has required providers to adopt EHRs that meet criteria for “meaningful use.” The criteria are complex, but the goal is simple: to ensure that the EHR in question is used in ways that can be measured significantly in quality and quantity.5 Those practices that meet the criteria could receive financial incentives; those that fail to do so could face financial penalties. By the end of 2014, about half (51%) of office-based physicians in the U.S. had adopted a basic 5 DHHS Centers for Medicare and Medicaid Services. 2015 Nov. Medicare and Medicaid Programs: Electronic Health Record Incentive Program; [accessed 2015 Nov 23] https:// www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/index. html?redirect=/ehrincentiveprograms

EHR, according to data from the federal Office of the National Coordinator for Health Information Technology (ONC). Roughly 76% of U.S. hospitals have a basic EHR with clinician notes.6 An overarching concern for PIAA insurers is that so many types of EHRs have been introduced and continue to be, frustrating the identification of EHR characteristics that could lead to problems. The large number of different EHR types makes it challenging for healthcare practitioners working in more than one health setting to proficiently learn multiple systems. Several organizations are studying why adverse events related to health IT are occurring and how to develop best practices to prevent them. Strategies for improvement are emerging. One source for analyzing and correcting possible patient safety issues is offered by the ONC Safety Assurance Factors for EHR Resilience (SAFER) Guides for EHRs.7 The ONC SAFER Guides comprise a set of self-assessment tools to help EHR users of all types.

ONC SAFER Guides The ONC SAFER Guides were developed by health IT safety researchers and informatics experts to provide self-assessment tools available to help proactively detect and reduce risks of error associated with EHRs. The nine guides address two foundational aspects of EHR implementation and use, three characteristics of the computing infrastructure, and four clinically focused, error-prone process categories identified through research and testing (Figure 2). Within each of the self-assessments are checklists of recommended practices based on the best evidence available at the time the guides were developed in 2013. The guides were field tested in a wide range of healthcare organizations, from small ambulatory practices to large health systems. 6 DHHS Office of the National Coordinator for Health Information Technology. 2015 Dec. HealthIT Dashboard, HealthIT Quick Stats; [accessed 2015 Dec 21] dashboard.healthit.gov/quickstats/quickstats.php 7 SAFER Guides for EHRs. 2014 Jan. DHHS Office of the National Coordinator for Health Information Technology; [accessed 2015 Oct 5] https://www.healthit.gov/safer/safer-guides


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Training Nearly one in five PIAA survey respondents said that one of the greatest challenges with EHRs is the education of its users. They ascribed many EHR patient safety issues to the inadequacy of initial instruction, lack of guidance when updates are input to the system, insufficient staff and peer group training, and inconsistent coaching for users across the organization or group. Training is a basic element in implementing a successful EHR system, according to ONC’s Safer Guides, but the logistics of training, especially when scheduling sessions for busy practitioners, can be a challenge. Clinicians should be trained and tested on basic EHR and CPOE operations before being issued login credentials, according to the SAFER Guides. The ONC SAFER narrative suggests that most organizations will want to start with the two self-assessment guides, High-Priority Practices and Organizational Responsibilities, within the Foundational category. The next step in using the guides would be to develop a plan based on the areas of greatest concern or interest that emerge from this first self-assessment. One of the goals of the ONC SAFER High-Priority Practices Guide is to ensure proper education of providers and other EHR users, suggesting that clinicians should be trained and tested on basic EHR and CPOE operations before being issued login credentials. This training should be monitored, provided promptly, and the organization should develop a process for assessment and feedback from users. One challenge in training users is the expectation to review the entire record. In the PIAA EHR Survey, the second most common type of MPL allegation cited by respondents

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was “claims alleging failure to review additional electronic records that were available.” The following case study offers an example of a claim involving EHR training. The case studies in this issue were provided to PIAA by David B. Troxel, MD, Medical Director of The Doctors Company (TDC), a California-based physicianowned medical professional liability insurer.

Case Study No. 1 Claim: EHR Training

A female presented to the ER with complaints of abdominal pain, nausea, and vomiting. An ovarian cyst had been removed two years prior. The emergency physician ordered an abdominal CT scan and called a gynecologist to evaluate the patient. The gynecologist reviewed a CT scan in the EHR that was later found to be the old scan showing the ovarian cyst. The patient was taken to surgery. No cyst was found. The patient developed a MRSA infection after surgery. The gynecologist had not been trained on the new EHR system and had not found the new CT scan that was available.

Patient Identification Recordkeeping and maintaining accurate patient identification are critical components to ensure patient safety with EHR use. For example, Patient ID errors can be a contributing factor in wrong-site surgeries, a category comprising surgery performed on the wrong side or site of the body, wrong surgical procedure, and surgery performed on the wrong patient. In the Joint Commission study of health IT-related sentinel events, wrong-site surgery was the second most common type of event, at 19%, after medication error (29%). (Joint Commission, 2015). Incorrect patient charting should be prevented to avoid a breach of data security and to ensure patient confidentiality and data accuracy. The Patient Identification Guide can help identify and evaluate where such breakdowns can occur.


The ONC SAFER Guides suggest that systems have a master patient index, which uses an algorithm that matches patient information, including first and last names, gender, date of birth, phone and Social Security numbers. The system generates an alert when a record is created for a new patient who shares the same first and last name as an existing patient. Any duplicate patient ID is monitored by the system. The system ensures that all data has been saved by checking for signatures before allowing personnel to exit the screen from one patient to another. This prevents lost data. Patient identity also should be verified at key points or transitions in the care process, for example at room assignment, when vital signs are recorded, entering surgery, and check-out, the Guides suggest.

Contingency Planning Hardware and software failures are a fact of life when using electronic systems. Although there can be several root causes of a failure, one that users can prepare for is electrical failure. Responses to the PIAA survey revealed that larger enterprises using EHRs have dedicated IT staff while smaller ones often have off-site facilities to obtain records via the web or cloud. Some have access to servers via secure data lines and/or generators for temporary access to back up files. Most revert to using paper charts during an interruption and later scan those charts into the system. The ONC SAFER Guides suggest redundant backup hardware to avoid problems that can occur when a system fails. Without those redundancies, delays in restoring use after failure can wreak havoc with business operations and patient safety and may lead to MPL claims. The ONC SAFER Guides also recommend duplication of mission-critical hardware systems, such as network routers, connection to the Internet, and database servers. System backup should be tested every month to ensure functional capacity. Data must be encrypted and backed up regularly and frequently, and transferred to an off-site storage location regularly to ensure safety. The Guides recommend that general staff and IT support staff work together to implement those recommendations. About 15% of EHR issues attributable to users occurred during EHR adoption, according to an analysis of claims by The Doctors Company.8 ONC’s Safer Guides suggest that hardware and software should be tested before and after going live, and especially when making modifications.

CMS to Phase Out Meaningful Use Requirements The federal Centers for Medicare and Medicaid Services (CMS) said Jan. 19 that it would move away from the Medicare Electronic Health Record Incentive Program, rolling its EHR incentives into a broader plan that links technology and quality improvement to clinician payments. The change is based on the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA))passed last fall. That law allows Medicare to transition from the staged meaningful use requirements to reward providers for the patient outcomes that technology helps them achieve. It offers clinicians more flexibility to customize Health IT to individual medical practice needs, and streamlines the process for granting hardship exceptions under meaningful use. The new law does not change EHR requirements for Medicaid. Rules governing MACRA are expected to be published this spring. CMS will consider quality, cost, and clinical practice improvement activities in determining Medicare physician payments. For now, however, the meaningful use requirement is still the law of the land.

8 Communication to PIAA from The Doctors Company. 2014. David B. Troxel, MD, provided an analysis of MPL claims closed from Jan 2007 through Jun 2014. Of those claims, 0.9% were EHR-related.


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Figure 3: Where to Begin? Issues that may increase patient safety risks have been identified in the following EHR tools and are discussed in ONC’s SAFER Guides.

Templates

Update continuously. Use evidence-based order sets for common procedures.

Drop-Down Boxes

Ensure that boxes reflect clinicians' particular practice patterns. Develop processes for alerts and audits.

Alerts

Alerts can assure a process for double-checking input accuracy, especially drug selection and dosing.

Autopopulation

Copy/ Paste

Clinical Decision Support Source: ONC SAFER Guides

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Check for auto-fill actions that may lead to incorrect medication names and/or dosing.

Require a process to track the original copied source and user; institute regular audits to identify issues.

Can help improve patient safety and care quality by decreasing human error and preventing omission of important data.

Systems also should be updated to reflect the evolution of medical knowledge. This should be done consistently to prevent outdated practices from permeating the systems thereafter, the Guides suggest.

Documentation The manner in which users enter data into the system is a major factor in MPL claims linked to EHR use. Figure 1 identifies the top allegation trends due to user error noted by PIAA respondents. Nearly 60% of PIAA survey respondents said they were aware of incidents in which EHR documentation was an allegation. At the root of many documentation issues is the fact that an electronic interface, as opposed to paper records, offers more limited choices and less opportunity for narrative. Users get frustrated when the EHR does not offer a choice that the clinician wishes to note, or space for further documentation. As one PIAA respondent noted, “No encoding system is adequate to capture the full information for many clinicians.” Many of the documentation errors identified by survey respondents involved standardized EHR features, including drop-down boxes, auto-population, and copy-and-paste. (See Jan. 15, 2015, Research Notes for an in-depth analysis of the survey.)

Templates Human error is inevitable, so templates must be designed to thwart those errors. PIAA respondents found that templates may pose problems especially if they are outdated, and should therefore be adopted with consideration. Respondents to the PIAA survey said they found several problems with templates, including that they were too generic, not intuitive and often led to inaccurate medical records. The ONC SAFER Guides recommend the use of evidence-based order sets and charting templates for common clinical procedures and


environments. The templates can help prevent medical personnel overlooking and/or inputting incorrect data. Following is a case example citing human error compounded by additional factors:

Case Study No. 2

Claim: Incorrect Drug Information in EHR A patient was seen by her cardiologist for hypertension. In the written medical record, her blood pressure medication had been increased to 25 mg once a day. Office staff entered the order into the EHR as twice a day. The prescription was filled. The patient missed her follow-up appointment. Seven months later, she went to the ER with numbness and weakness. Her potassium level was low. The cardiologist corrected the prescription error and gave her potassium.

Users Bypassing the System In the PIAA survey, more than half of respondents (53%) said they had experience with providers bypassing the EHR system, circumventing safety features and developing work-arounds. Examples include instances of users turning off warnings and alerts, selecting an incorrect option in dropdown fields because of time constraints, and failing to resolve a chief complaint in the EHR before the patient is discharged. Respondents also said they had seen instances where providers entered medications not listed in the system, failed to save a new medication order so the system would revert to an original order, or simply ignored alert features.

Drop-Down Boxes The drop-down box, common in many online forms, is also troublesome for EHRs. Dropdown boxes do not lend themselves to fields where the number of choices is extremely

large. Yet offering a limited selection may not satisfy clinicians. Many EHR systems do just that, and the limited choices on offer can lead busy clinicians trying to document under time pressure to make inadequate choices, PIAA survey respondents noted. The following case studies suggest MPL claims arising from documentation issues:

Case Study No. 3

Claim: Insufficient Area for Documentation, Drop-Down Menu A female had a bladder sling inserted for urinary incontinence. Her surgeon was assisted by a proctor surgeon representing the product manufacturer and training the patient’s surgeon on the procedure. The patient was informed that another physician would be assisting. In the recovery room, there was blood in the Foley catheter, so the patient was returned to surgery. The bladder had been punctured by the sling. The proctor had approved the sling’s placement. The circulating nurse did not document the proctor’s presence in the OR due to lack of an option in the EHR drop-down menu. There was no space for a free-text narrative to document that the patient was informed of the proctor’s presence.

Case Study No. 4

Claim: Drop-Down Menu A patient was seen by her physician for pain management with trigger point injections of opioids. The physician ordered morphine sulfate (MS) 15 mg every eight hours. In the EHR, the drop-down menu offered MS 15 mg while the next option on the list was MS 200 mg. The physician inadvertently selected MS 200 mg and did not recheck before completing the order. The patient filled the prescription, took one MS along with Xanax, and developed slurred speech—resulting in an ER visit with overnight observation.


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Alerts and Auto-Population Auto-population—an automated feature used to complete a long word the user is typing—is a source of contention. On one hand, it can make data input quicker; on the other, it creates a greater chance for error if the user does not realize that certain bits of information have been auto-populated incorrectly. PIAA respondents had several issues with auto-population, citing mistaken entries, inappropriate context, and cases of autopopulation of fields with data from different patients with the same name, among others. To thwart possible problems with autopopulation, EHR systems have support features, including warnings, suggestions, and information buttons. The ONC SAFER Guides recommend the use of those available features, which are interactive, but also propose double-checking the output for accuracy. Alerts can help reduce the risks of ordering contraindicated, non-therapeutic, or incorrect doses of medications, the ONC SAFER Guides note. Other key features include: alerts for abnormal lab results, drug-allergy checks, drug-food interaction checks, and other alerts as needed. A reverse allergy check could alert when a new allergen is entered into a patient’s record. Drug-dosing support can include the minimum and maximum doses, as well as renal, weight-based, and age-appropriate doses. The next case example involves autopopulation and alert factors:

Case Study No. 5 Claim: Lack of EHR Drug Alert An elderly female saw an otolaryngologist for ear/nose complaints. The physician intended to order Flonase nasal spray. Patient

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filled the prescription and took it as directed. Ten days later, she went to the ER for dizziness. Two weeks later, the pharmacy sent a refill to the physician at his request. It was for Flomax (for enlarged prostate)—which has a side effect of hypotension. When ordering, the physician typed “FLO” in the medication order screen. The EHR auto-matched Flomax, and the physician selected it. Flomax is not FDA-approved for females. There was no EHR drug alert available for gender.

Copy and Paste EHR users can easily duplicate information in the patient record by using the copy and paste function. However, the challenge comes with improper use of this tool, which can have potential MPL claim implications. Copy and paste practices, at 71%, were by far the most common allegations noted by PIAA survey Copy and paste practices, at 71%, were by far the most common of allegations noted by PIAA survey respondents. respondents. Copy and paste ranked third in the top issues attributed to EHRs users within the claims database analyzed by TDC. ECRI Institute in 2015 convened a workgroup on the copy/paste issue, which included representation from the PIAA Research Department, to identify best practices to track instances where copy/paste is acceptable in an EHR and to encourage improvements that can ensure patient safety. Also in 2015, the institute published a special report on the prevalence of copy and paste use, problems it may present and best practices to limit them.


Verifying the accuracy of the material copied, acknowledging the original source of the copied data, systems that can track copy and paste use over time, and regular audits are suggested. The next case study involves a situation in which copy and paste patterns caused an oversight that resulted in a negative outcome:

Further Reading

Claim: Copy and Paste

Partnership for Health IT Patient Safety. 2016 Feb. Health IT Safe Practices: Toolkit for the Safe Use of Copy and Paste. [accessed 2016 1 Mar] https://www.ecri. org/resource-center/Pages/ HIT-Safe-Practices.aspx

A toddler was taken to a country where tuberculosis was prevalent. After the trip, he presented with fever, rash, and fussiness. The physician considered bug bite or flu and treated the child with fluids, antibiotics, and flu meds. His office EHR progress note indicated there was no tuberculosis exposure. The physician copied and pasted this information during subsequent office visits with no revision to note travel to a country with tuberculosis. Two weeks later, the child was diagnosed in the ER with tuberculous meningitis. He had permanent and severe cognitive defects.

Graber M et al. 2015 Nov 6. Electronic Health RecordRelated Events in Medical Malpractice Claims. Journal of Patient Safety; [accessed 2016 Feb 25] http://journals.lww. com/journalpatientsafety/ Abstract/publishahead/ Electronic_Health_Record_ Related_Events_in_ Medical.99624.aspx

Case Study No. 6

Clinical Decision Support This feature of many EHR systems can help improve documentation issues, according to ONC’s Safer Guides. The use and implementation of clinical decision support is complex, and requires maintenance to function properly, but it can improve patient safety and quality of care by decreasing human errors and preventing the omission of important data and information—all of which could result in patient harm and MPL claims. Unfortunately, many EHR systems do not have robust decision support features, and clinical decision support must either stand alone or be integrated as an add-on to an existing EHR system. The Computerized Provider Order Entry (CPOE) with Clinical Decision Support ONC SAFER Guide is devoted to a self-assessment of clinical decision support with the goal of optimizing its safety and use. Relying on the technology alone is insufficient to support and manage the complex processes related to CPOE with clinical decision support, ONC SAFER contends, and can lead to potential safety risks. Partial adoption of CPOE or a lack of its monitoring can result in hazardous conditions. A key step is to create a multidisciplinary team with clinician leadership to assess whether and how particular recommended practices affect the organization’s ability to deliver safe, high-quality care, the ONC’s SAFER notes.

Sittig D, Singh H. 2015 Jul 21. The Health IT Safety Center Roadmap: What’s Next? Health Affairs Blog; [accessed 2016 Mar 3] healthaffairs.org Banger A, Graber M. 2015 Feb. Recent Evidence that Health IT Improves Patient Safety. DHHS Office of the National Coordinator. [accessed 2015 Dec 8] healthit.gov Partnering for Success. 2014 Sep 23. Partnership for Health IT Patient Safety; [accessed 2015 Dec 12] www.ecri.org Ruder DB. 2014 Jan/Feb. Malpractice Claims Analysis Confirms Risks in EHRs. Patient Safety & Qual Healthcare. www.PSQH.com Metzger J, et al. 2010 Dec 22. Mixed Results in the Safety Performance of Computerized Physician Order Entry. Health Affairs. www.healthaffairs.org Singh H, Ash JS, Sittig DF. 2013 Apr. Safety Assurance Factors for Electronic Health Record Resilience (SAFER): study protocol. BMC Med Inform Decis Mak. https:// bmcmedinformdecismak. biomedcentral.com/


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Summary As EHR use is rising, so are MPL claims linked to the technology. As we continue to identify problems, we need to track the cause of those issues and share mitigation strategies. System inefficiencies, human error in inputting and double-checking data, and errors in clinical content are major factors that must be identified and corrected. The goal remains to continually improve the safe use of EHRs and health IT. ONC’s SAFER selfassessment Guides offer tools that users can utilize to help ensure continuous improvement in EHR systems so that perhaps eventually EHRs can offer the benefits of increased productivity and lower cost that have been promised. However, the ONC SAFER Guides cannot, in and of themselves, ensure the safe use of EHRs. Health IT was cited for the most part as a vulnerability or latent factor in the Joint Commission’s analysis of sentinel events. Importantly, the SAFER Guides emphasize the need for collaboration among clinicians and staff—administrative, technical, and clinical. Recognizing and reporting potential EHR hazards necessitates “situational awareness” by all involved.

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“It is not always easy to unravel the sociotechnical complexity of EHR events and much more research needs to be done on the issues and solutions to them,” according to Hardeep Singh, MD, MPH, Chief of Health Policy, Quality and Informatics with the Veterans Affairs Health Services Research Center for Innovations in Houston. In addition to the sociotechnical element, organizational culture could be critical to reducing errors linked to EHRs and continuously improving those systems. Citing research by its CEO Mark Chassin, MD, the Joint Commission report concludes, “Recognition involves not only identification of health IT-related hazards but also recognition of the potential patient harm that could result if the hazard is not mitigated. This can only be successful in organizations with a strong patient safety infrastructure characterized by a culture of safety where hazards and close calls (“near misses”) are routinely reported, process improvement is comprehensive and systematic, and leadership acts upon the identified issues in a timely manner,” (Joint Commission, 2015).


Special Guest Editor

David B. Troxel, MD, Medical Director, The Doctors Company PIAA invited Dr. David B. Troxel of The Doctors Company to comment on his research and experience with EHRs. Dr. Troxel contributed the case studies linked to EHR use mentioned in this report. In addition, his company provided an analysis of closed claims reported here. The Doctors Company reviewed closed MPL claims over a period of 7.5 years. Of those claims, EHR-related factors were found in 0.9%, or 97. User factors contributed to 58% of the EHR-related claims while system factors were linked to 42% (Figure 4).

Fig. 4: Top Issues Attributed to EHR Users Incorrect Information in the EHR 16% 42%

15% 13% 7%

7%

Hybrid Health Records/ EHR Conversion Prepopulating/Copy and Paste EHR Training/Education EHR User Error (other than data entry)

Source: The Doctors Company

Other

Other experts in health safety and technology were asked to review and offer their expertise in the development of this paper. We acknowledge and thank them for their time and effort in assisting with this endeavor. Many thanks to Dean Sittig, PhD, Professor, School of Biomedical Informatics at The University of Texas Health Science Center, Hardeep Singh, MD, MPH, Chief, Health Policy, Quality and Informatics Program, Houston Veterans Affairs Health Services Research Center for Innovations, and Kathy Kenyon, JD, formerly with the ONC, and now with Kenyon Law Firm, Billings, MT.

Our Expertise Is Medical Liability. Our Passion Is Quality Healthcare.

The PIAA Research Department prepared this news letter. This information is not intended to be, nor should it be, interpreted as being a standard of care. Com ments or corrections should be forwarded to the editors: Pamela Taulbee, Research Associate, at [email protected] or P. Divya Parikh, Vice President of Research & Risk Management at [email protected]. If you would like to cite any material from Research Notes, please complete a Citation Request Form, which may be downloaded from www.piaa.us under Data Sharing Project/Contact Us. Return the form by mail, fax or email. Copyright © 2016 PIAA. All rights reserved. PIAA, 2275 Research Blvd., Suite 250, Rockville, MD 20850. www.piaa.us


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