The Influence of a Specific Ophthalmological Electronic Health Record on ICD-10 Coding

Healthcare providers increasingly implement Electronic Health Records (EHR) in their hospitals [1]. Evidence is available that EHR helps deliver better healthcare and to increase cost-effectiveness [2]. In most situations, a Hospital Information Systems (HIS) is linked to an Enterprise Resource Planning software (ERP). For administrative reasons and cost reduction, many institutions focus on one comprehensive EHR system and refuse to use specialized subsystems. Typically, most software solutions only allow the sufficient recording of general medical and surgical data that are not specific for respective specialties. Capturing special data effectively in small specialties such as ophthalmology is not supported usually. This is especially unfortunate, as ophthalmology is a subspecialty with a large number of outpatients generating a huge amount of numeric data (e.g., visual acuity, and intraocular pressure). A recent study has identified ophthalmology together with dermatology and psychiatry as being the medical specialties with the lowest use of EHRs [3].

Recently, governments have started to offer incentives for the introduction of EHRs. To date, many countries worldwide use the International Classification of Diseases (ICD) version 10 coding. The employment of an EHR is of utmost importance for the proper digital coding of diseases. German hospitals have been obliged to code every admitted case by using ICD-10-based diagnoses since the year 2000. A German modification (ICD-10-GM) has been used since 2004 and differs from the original suggestion of the World Health Organization (WHO) in the suffixes. The ICD-10-clinical modification (CM) proposed by the American Center for Disease Control and Prevention (CDC), which has been used in the USA only since October 2015, is also slightly different from the first WHO proposal [4].

In 2004, HIS (i.s.h.med, Cerner GmbH) was implemented at the University Hospital of the Ludwig-Maximilian University (LMU) in Munich for administrative purposes. The Department of Ophthalmology of the LMU is a major regional academic ophthalmic healthcare provider with over 65,000 outpatient and 12,000 inpatient cases annually. As no specific ophthalmological user interfaces were available for the used HIS, a team of ophthalmologists and computer scientists started to adapt this system for effective use in the department in 2012. The expectation was to increase efficiency by instant access to medical documentation and to avoid time-consuming searches for missing files. As the number of patients continues to increase, an optimized workflow supported by the corresponding digital processing of their data is needed. Furthermore, special attention was paid to developing a medical-user- and clinical-workflow-orientated software, concurrently capturing as much administrative data as possible (e.g., ICD-10). Proper coding quality is not only relevant for reimbursement, but also offers a great opportunity for retrospective research in a short time, as digital data is easily and quickly available. Patients also benefit from good coding quality as they can be asked to participate in clinical trials, and other treating physicians can maintain an overview of correct diagnoses.

The aim of this study is to evaluate the change by numbers and diversity in recorded ICD-10 diagnoses because of the implementation of a specific ophthalmological EHR system. Moreover, the change in the number of patients has been analyzed pre- and post-EHR introduction.

The introduction of the EHR optimized for ophthalmology led to a significant increase in the variety and number of documented diagnoses in our outpatient cases during the observational period.

We observed a significant change in the variety of coded diagnoses by the number of different diagnoses used per week (156.2 (+/−30.2 SD) vs. 186.8 (+/−15.3 SD)). As an online catalog with a full text search was available now, this option was probably used more often, leading to a more diverse coding behavior of the staff. Before this, with the old web-based software, only a very limited number of keywords could be used. When paper charts were still used, there was no need for a doctor to be logged into a PC, although they were available at any exam room. Consequently, the web-based tool was not used. Doctors may have used memorized ICD-10 codes. Rarer diagnoses codes may not be remembered by heart.

Before the introduction of the digital recording system, the administrative staff entered the diagnoses manually by transferring the code into the HIS that was hand-written in a file by the physician. However, vague codes such as “Z01.0,” which is “visual acuity testing,” were regularly entered in order to have at least one code with which to close the case and to fulfill requirements for the reimbursement. Sometimes, a physician did not provide a diagnosis in the paper chart. Moreover, in this situation, a Z01.0 diagnosis was possibly entered by hospital clerks. Notably, the number of diagnoses does not influence the amount of reimbursement for outpatients in Germany. The introduction of the digital system caused a sharp drop in this “wildcard” diagnosis (Table 1).

As the number of diagnoses per outpatient case also went up, the previously rarely documented diagnoses such as Z96.1 (presence of an intraocular lens implant), were used more often. The second largest increase in all diagnoses was related to lenses (ICD-10: H25-H28). Either of the two conditions (including aphakia H27.0) exists in every human. This is probably because more diagnoses are coded for every patient, and the lens status of a patient is documented more often.

The largest increase of diagnoses categories was in coding for choroidal and retinal diagnoses. The Department for Ophthalmology of the University of Munich is a specialized center for these kinds of maladies. Another confounder might be the increase in the number of patients being treated by intravitreal injections because of diseases such as age-related macular degeneration (AMD). In addition, early onset forms of AMD occur in many older patients. Meticulous physicians might have also coded this diagnosis, even though no treatment is necessary for it yet.

Rarer diagnoses such as corneal diseases (ICD-10 H15-H22) were probably coded more often, as the new online search engine offers a better tool for finding an appropriate diagnosis than the previously used self-made tool. It also contains an automatic correction for typographical errors and offers the most suitable diagnosis in cases for which no unique ICD-10 code for the medical condition is available.

One key issue in ophthalmology is the present lack of accuracy of ICD-10 in many ophthalmological diseases. Considerations were made in the past to differentiate ICD-10 coding further, but this has not been implemented as yet [9]. For example, all forms of AMD, be it neovascular AMD (“wet”) or geographic AMD (“dry”), are coded as H35.3 in ICD-10, although treatment approaches and courses of diseases differ greatly [10]. For clinical studies, a more detailed classification is necessary. To achieve this, the World Health Organization (WHO) currently proposes an ICD-11 draft online in which professionals are asked to participate and give their input for a more precise and up-to-date classification of diseases [11]. At present, the ICD-11 draft includes its own subgroup for macular diseases (ICD-11: AG40).

Before the introduction of EHR, differences in diagnoses per case between scheduled patients and emergency patients were minimal (1.10 vs. 1.15). Once EHR was implemented, diagnoses of emergency unit patients increased to 1.20 diagnoses per case. In scheduled patients, the increase was even more intense: It went up from 1.08 to 1.47 diagnoses per case. Two explanations for this finding could be: (1) the complexity of scheduled patients in an academic center and (2) the consultants now being part of the coding process to close the case. An emergency care of patients is often more straightforward. Additionally, residents often treat only emergency patients, especially in less complex situations in which a single diagnosis is usually sufficient.

A major concern raised by critics about EHR is the increase in the time needed for documentation and the consecutive reduction of patient treatment time, resulting in reduced numbers of patients treated [12]. However, the introduction of the digital system did not result in a decay of treated patients in our department; on the contrary, the overall number of treated patients increased by 5.97 %. The general higher case numbers can cause an increase in the total number of diagnoses per period but will not alter the number of codes per case. The medical workforce in our department was not altered during the study period. One explanation for the increased patient numbers could be that, in the second period, every consultation had to be documented digitally, which is only possible, if a valid visit in the HIS on that day occurs. Before the introduction of an EHR, consultations without valid cases in the HIS might have taken place.

At present, not all of the subspecialties covered in our department are integrated into the digital system [6].

As the EHR training of staff took place, it might have led to a bias in the results, although neither any specific education on diagnoses coding was provided for any staff group nor were the advantages of coding promoted. It might be possible that training caused more attention to proper coding. Another limitation of this study due to labor privacy laws in Germany was that we were not able to investigate the individual physician’s contributions to the coding changes, which in theory could explain some of the changes in coding found in this manuscript.

In this study, we have demonstrated that a significant shift occurs in diagnoses after the introduction of an EHR. The number of diagnoses per case rise significantly in emergency department patients. In addition to the change in numbers, the diversity of diagnoses alters. For research purposes, it is advantageous to have as many precise diagnoses recorded as possible. It will greatly facilitate queries in an EHR for patients. In the future, many possibilities may arise when using EHR data for research [13, 14, 15].

ABAP, advanced business application programming; AMD, age-related macular degeneration; COBOL, common business oriented language; EHR, electronic health record; ERP, enterprise resource planning; ETDRS, early treatment of diabetic retinopathy study; GUI, graphical user interface; HIS, hospital information system; ICD-10, international classification of diseases version 10; ICD-10-CM, international classification of diseases version 10 clinical modification; ICD-10-GM, international classification of diseases version 10 German modification; ICD-11, international classification of diseases version 11; LMU, Ludwig-Maximilian University Munich; PMD, parametric medical documents; SD, standard deviation; WHO, World Health Organization