EHRs Benefits and Drawbacks

The electronic health record as a catalyst for quality improvement in patient care Thomas H Payne

Department of Medicine, University of Washington, Seattle, Washington, USA

Correspondence to Dr Thomas H Payne, Medicine IT Services, Box 359968, 325 Ninth Avenue, Seattle, WA 98105, USA; tpayne@u. washington.edu

Received 4 April 2016 Revised 6 July 2016 Accepted 7 July 2016 Published Online First 8 August 2016

To cite: Payne TH. Heart 2016;102:1782–1787.

ABSTRACT Electronic health records (EHRs) are now broadly used, following decades of development and incentive programmes for their use. EHRs have been shown through use of reminders, electronic order sets and other means to improve reliability of performance of many basic tasks in acute, preventive and chronic care. They assist with collecting, summarising and displaying the large volumes of information in patient records and support the implementation of guidelines and care pathways. Broad use of EHRs has brought into focus weaknesses of the current generation of EHRs: their user interface, implementation difficulties, time required to use them and others. Addressing these weaknesses and adopting new technologies, including use of voice, natural language processing and data analytic techniques, is necessary for EHRs to achieve their full potential: to gather information from routine care, to learn from it and to be an integral component of efforts to continuously improve and to transform care.

INTRODUCTION Electronic health records (EHRs) have been regarded as an integral component of healthcare transformation1 and since large programmes in the UK2 and the US American Recovery and Reinvestment Act of 2009 financial incentives3

have become an important part of daily practice for physicians in many countries. The rapid transi- tion from paper to EHRs has resulted in substan- tial change in practice, with mixed reception among physicians.4

What evidence drove the vision that EHRs are the key to healthcare transformation? Should this vision be changed and if so in what ways? In this paper we provide an overview for the rationale of moving to EHRs and the ways they can be lever- aged to improve the quality of care we deliver. EHRs, sometimes referred to as electronic

medical records, are computing systems that replace and expand functions previously provided by paper medical records: to document care, review patient data from the laboratory, imaging, clinical studies, patient experience and other sources and to enter and communicate orders. Beyond this, EHRs permit communication within the patient care team including the patient in ways paper could not and permit us to study and manage care of populations, to bill for care, potentially to learn from pooled EHR data and other functions (table 1). The term ‘system’ indicates that EHRs are

usually not single applications but rather multiple applications and databases connected into a larger and more complex whole. They often using web portals and devices at the point of care,

connections to patient-monitoring devices and sometimes remotely stored database management systems. The earliest EHRs were referred to as computer-based medical record systems6 and were mostly the product of academic and research devel- opment groups in the hospitals and clinics where they were developed. Today most, with very few exceptions,7 8 are commercial systems licenced from vendors in a market stratified by their focus on inpatient or outpatient care and dominated by a small number of vendors.

PROBLEMS THAT EHRS CAN HELP SOLVE The quality of medical care is multifaceted and includes as its foundation the reliable performance of many basic tasks. The detail involved in these tasks is ‘work humans neither relish nor reliably perform’,9 in part because of limitation of our memory and attention, which computing systems can help address.10 Among the earliest demonstra- tions of the ability of EHRs to improve reliable per- formance arose over 40 years ago from efforts to manage positive strep throat cultures.11 In this early study, reminders were sent to providers of patients who did not have documented treatment of positive cultures within 10 days. These remin- ders reduced rates of untreated positive cultures dramatically, but more importantly this effect seemed not due entirely to education: when the reminders were removed, rates of untreated cul- tures returned to their previous level (figure 1). This is because when facing the demands of busy and sometimes chaotic clinic practice, computerised reminders helped providers remember to follow through with care they intended to provide; without reminders, 1 in 10 patients were untreated after 10 days. This beneficial effect of EHRs has been observed

repeatedly in various domains such as instituting antimicrobial prophylaxis in immunocompromised patients,12 general preventative care13 and in care of patients with chronic illness.14 The weight of evi- dence suggests that such reminders work and augment human tendency to forget details (figure 2). EHRs also help store, manage and deliver infor-

mation in volumes that exceed human abilities and permit multiple clinicians to simultaneously access the same patient record from different locations. As volumes of health information have risen geomet- rically driven by imaging and genomic information and vast collections of text and other data, the storage, information summarisation and communi- cation strengths of EHRs have led most to believe that reverting to a paper record is now impractical. Limitations in human cognition and the amount of information we can simultaneously consider when

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making decisions may present an upper limit beyond which some external support will be needed (figure 3).15

The patient safety movement was energised by the Institute of Medicine’s publication To Err is Human,16 in which EHR cap- abilities were highlighted and recommended, such as the use of computerised practitioner order entry (CPOE) with immediate checks to avoid errors. In an early and seminal study, CPOE was associated with 55% reduction in serious adverse medication errors.17 Other studies have shown benefit in dosage adjustment for patients in renal failure and in other domains.18 Embedding patient care guidelines in order sets—collections of electronic orders that simplify and speed ordering—has been demonstrated to improve adherence with guidelines because it is much simpler to do so and fits within ordering workflow,19 including highly complex chemotherapy protocols. Guidelines embedded in order sets can be easily updated and disseminated. Some medi- cation errors occur at the time of medication administration at the bedside; bar code medication administration has the poten- tial to reduce these errors.20

As national healthcare systems turn to risk-sharing and quality reimbursement models to manage the health of a population of patients, patient care information management needs rise by several orders of magnitude. Paper medical records are ill-suited to this task: maintaining and continuous updating records of millions of patients is only possible when health information is in electronic form.

Nowhere are volumes of patient information higher and the need for information management greater than in critically ill patients. Volumes of patient history and observations, non- invasive and invasive monitoring information, imaging, labora- tory testing and other data are enormous in the most critically ill patients. Health information technology, including EHRs but extending beyond to include imaging systems, picture archiving and communication systems, bedside devices and other forms, is

invaluable for decision-making.21–24 EHRs are interfaced to these systems, providing a more unified view of the patient.

We now have early steps towards leveraging EHRs to better measure and improve quality,25 though formidable challenges remain.26 27 However, quality of patient care is more than avoiding errors and attending to details. It includes making the correct diagnosis.28 Aiding clinician diagnostic judgement has been for many years viewed as a difficult task and in some cases beyond capabilities of current computing systems because of the broad range of facts to be considered.29 Early experiments in leveraging that information for reasoning and application of artificial intelligence did not reach broad use,30 but there is renewed work in diagnostic decision support using systems closely linked to data on patient symp- toms, physical findings and test results gathered in the EHRs.31 All this is dependent on capturing detailed elements of history, examination and other findings in machine- processable form.

Table 2 summarises key articles and reviews of EHR function- ality for improving care and the evidence regarding its effectiveness.

NEW EHR TECHNOLOGIES Several trends will contribute to our ability to leverage rising computing power and information volumes to address health- care quality improvement.

Analytics With the medical records in electronic form, there is a potential to leverage enormous growth in computer processing power to analyse patient information and to act on the results. Simple reminders based on the above-mentioned algorithms are an early form of potential predictive analytics extend these capabil- ities to finding associations and correlations between data within one patient’s record or across millions of records in a fashion that has proved valuable for other large collections of data.46

Today the main barrier is capturing information from clinicians without disrupting their workflow or requiring excessive time and in capturing patient information dispersed across many EHRs and other computing systems and devices. The data within EHRs, particularly the large proportion in narrative text and stored images, are used for human review but not for its full potential. This will likely change because of continued growth in other technologies.

Voice technologies Voice recognition software is increasingly accurate and available both in handheld devices and EHRs. It permits use of voice as an alternative to keyboard and mouse for documenting care in notes and reports, which appeals especially to the large percent- age of physicians who are not expert typists.47 Using voice to enter a note most often results in unstructured or narrative text,

Figure 1 Graph showing the effect of reminders on the percentage of patients with recorded treatment for positive group A β-haemolytic strep throat cultures.11

Table 1 Typical functionality of EHRs in use today5*

Results review (lab, path, imaging, notes) Quality metrics, dashboards

Documentation (direct entry, structured unstructured, dictation, mixed)

Electronic communication With team With patients

Order management Patient monitoring review Patient summary displays Patient support Medication administration record Population health Bar code medication administration External reference resources Patient lists, schedule, rounding/handoff tools Administration and billing

*This list is an extension of the list from Institute of Medicine Committee on Data Standards for Patient Safety, Key Capabilities of an Electronic Health Record System, Letter Report, Washington DC: The National Academies Press, 2003. EHR, electronic health record.

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rather than structured or coded information entered using a mouse to select from dropdown lists or radio buttons. Narrative text familiar to humans must be converted to a machine-

processable encoded form in a way that preserves meaning in order to leverage computing technologies.

Natural language processing Natural language processing is a subfield of artificial intelligence and computational linguistics used for studying the problems of automated generation and understanding of natural human languages. It is used to capture meaning within text generated by spoken voice or other narrative text and then in conjunction with other methods to represent that meaning so that it can be processed and interpreted by computing systems.48

Representing information and knowledge is in itself an complex problem: simple listing of data as in a spreadsheet can be enhanced by creating links between data elements, synonyms and attributes of the data and of the linkages between them.49

Doing so can preserve the information contained within a patient history, discharge summary or narrative procedure report. The meaning of phrases indicating concept negation or qualification, such as ‘denies chest pain’ and ‘probable aortic stenosis’, is preserved.

Figure 2 Median absolute improvements in adherence to processes of care between intervention and control groups in each study are shown. Each study is represented by the median and IQR for its reported outcomes; studies with single data points reported only one eligible outcome.14

Figure 3 Schematic representation depicting the increase in number of facts per clinical decision with new sources of biological data.15 SNP, single nucleotide polymorphism.

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EHR architecture Change to EHR architecture is also underway. Despite myriad shortcomings of commercial EHRs, their millions of lines of computer code embody the results of decades of work by vendor teams and customer innovations and feedback. Can core EHR systems be leveraged by other developers, who are not connected with the EHR vendor except through use of shared open stan- dards, or by the public at large? One promising way to do this is by developing standards such as the Fast Health Interoperability Resource, a draft standard from the Health Level 7 standards organisation,50 which permits other developers to create applica- tions that build on, extend and improve EHRs.51

Linking EHRs with other databases Health data within EHRs may be linked with national mortality databases, medical registries, drug prescription files and environ- mental exposure databases to provide insights not possible separately.52

Patient involvement Much of EHR development and investment has been devoted to the small percentage of life spent in an acute care facility or clinic, but until recently without substantial support for where people live. Personal health records, patient portals and greater

patient involvement in their record are all growing rapidly.53

Patient contribution of self-monitoring, vital signs and outcome measurements can provide a fuller, more accurate health record.

ADDRESSING EHR WEAKNESSES This listing of real and potential EHR capabilities is not materi- ally different from those described a quarter century ago.54 What is clearer today are EHRs’ weaknesses, highlighted recently not only by broad EHR adoption by technology-avid pioneers and developers, but by the majority of physicians, nurses and other health professionals. Most clinicians require hours of training to use them safely, many feel EHRs usability lags behind technology in other sectors of society55 and that EHRs require too much time to use56 and contribute to professional dissatisfaction.57

CPOE also has the potential to introduce errors and requires extra time for physicians.58 Both the public and physicians have raised concerns about privacy of EHR data and limitations of anonymisation of data.59 Broad EHR adoption has been very dif- ficult and expensive in the USA and the UK.60 61

Difficulties with EHR documentation include time require- ments, risk that the patient story is lost or, on the other hand, that narrative notes may not contain data needed to improve care quality.62 Possible solutions include capturing high-value data that patients can often enter as well or better than

Table 2 EHR capabilities for improving care and their impact. Key articles and reviews

Key findings References

Decision support General Evidence suggests that some CDSSs can improve physician performance and use of CDS and computerised

provider order entry.

32 33

Many CDSSs improve practitioner performance and healthcare process measures across diverse settings. The effects on patient outcomes remain understudied and, when studied, they are inconsistent. Evidence for clinical, economic, workload and efficiency outcomes remains sparse.

34 35

Recommendations for improving decision support 36

Reminders General Computer reminders produce care improvements, though less than generally expected from the

implementation of computerised order entry and electronic medical record systems.

14

Preventive care Reminders improve timeliness and completeness of preventive care interventions. 12 13

Chronic illness Process benefits are easier to achieve than outcomes benefits, especially for chronic diseases. 37

CPOE Adverse drug events risk Risk of serious adverse drug events is reduced by 55%. 17

Adverse drug event events and outcomes CPOE with CDS can improve patient safety and can lower medication-related costs. Few studies measured the effects of CPOE and CDS on rates of adverse drug events and none of the studies were randomized controlled trials.

18 38

Appropriate imaging ordering Computerised CDS integrated with the EHR can improve appropriate use of diagnostic radiology by a moderate amount and can decrease the use by a small amount.

39

Ordering of appropriate anti-infective A computerised anti-infective management programme can improve outcomes and reduce costs. 23

Effect on anti-infective time of delivery Implementation of an electronic order-management system improved the timeliness of antibiotic administration to critical-care patients.

40

Complying with patient care guidelines EHR order sets can increase compliance with care guidelines. 19

Diagnostic accuracy Differential diagnosis Experimental diagnostic systems performed as well as clinicians in some domains. 41

Diagnostic decision support Diagnostic HIT research is still in its early stages with few demonstrations of measurable clinical impact. 42

Therapeutic recommendations Early systems provide advice on lymphoma treatment similar to the treatment provided in a university oncology clinic.

30 43

Use in the ICU EHRs have not been shown to have substantial effect on ICU mortality, length of stay or cost. 21

Record visualisation and summarisation Application of data visualisation techniques to EHRs is currently limited by data complexity and incompleteness, but there is growing research to leverage ‘big data’ techniques to patient data.

44

Population and public health EHRs can expand the role of current surveillance efforts and can help bridge the gap between public health practice and clinical medicine.

45

CDS, clinical decision support; CDSS, clinical decision support system; CPOE, computerised practitioner order entry; EHR, electronic health record; HIT, health information technology; ICU, intensive care unit.

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providers and appropriate mixture of narrative and encoded data.63 Addressing documentation problems may require changes to regulation and reimbursement models (eg, EHR vendors support current evaluation and management rules in the USA), broadening documentation requirements for reim- bursement from the entire healthcare team including the patient and not just the physicians.64

Particularly relevant to this discussion is that alerts and order checks are not well accepted.65 66 Most alerts for drug-drug interactions—one of the most common alerts clinicians experi- ence—are based on simple logic that does not consider labora- tory results, age or provider response to prior similar alerts. Improving decision support requires underlying rules that reflect patient and provider characteristics and use of more detailed and complete patient data. Table 3 summarises recent reports that propose EHR improvements.

VISION The transition from paper to electronic records has largely occurred in many countries. We now need a more efficient, comfortable clinician-user-EHR interaction with EHR features that augment human strengths so that the EHR captures the full history of health, illness and impact of treatments and also sub- stantially helps us improve the care we deliver. With such an EHR we can potentially learn immensely from countless visits, hospitalisations, procedures and even more from the everyday experience of people in health and disease, as captured in the EHR. We can apply what we learn to decision support that is ‘smarter than the doctor’, to automated diagnostic assistance and to data analytics that offer insights not previously possible.

Unifying models for improving care include the concept of a learning healthcare system70 where information gathered in the EHR in the process of care loops back to improve health and care delivery with little delay. The learning healthcare system calls for feedback and analysis of enormous volumes of infor- mation to complement the view provided by today’s controlled clinical trials. Imagine capitalising on and supporting what physicians do best without unduly detracting from time spent with patients, yet continuously analysing the records to measure and inexorably improve care. This is the potential of EHRs: to serve as an integral part of our efforts to improve and to transform care.

Competing interests None declared.

Provenance and peer review Commissioned; internally peer reviewed.

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Table 3 Recommendations for improving EHRs and their implementation

Topic Year(s) References

Improving key functionality Usability 2013, 2016 55 67

Documentation 2013, 2015 62 63 68

Drug-drug interaction alerts 2016 69

Decision support 2003 36

General EHR improvements EHR 2020 2015 64

Addressing difficulties with implementation NHS secondary care 2011 61

EHR, Electronic health record; NHS, National Health Service.

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