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Can a health information exchange save healthcare costs? Evidence from a pilot program in South Korea
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Can a health information exchange save healthcare costs? Evidence from a pilot program in South Korea Hayoung Park a , Sang-il Lee b , Hee Hwang c,∗ , Yoon Kim d , Eun-Young Heo e , Jeong-Whun Kim f , Kyooseob Ha g a
Technology Management, Economics, and Policy Graduate Program, Seoul National University, 1 Kwanak-ro, Kwanak-gu, Seoul 151-015, Republic of Korea b Department of Preventive Medicine, College of Medicine, University of Ulsan, 86 Asan Byungwon-gil, Songpa-gu, Seoul 138-736, Republic of Korea c Department of Pediatrics, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea d Department of Health Policy and Management, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul 110-799, Republic of Korea e Department of Medical Informatics, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea f Department of Otorhinolaryngology, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea g Department of Psychiatry, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea
a r t i c l e
i n f o
a b s t r a c t
Article history:
Objective: Governments and institutions across the world have made efforts to adopt and
Received 20 January 2015
diffuse the health information exchange (HIE) technology with the expectation that the
Received in revised form 6 May 2015
technology would improve the quality and efficiency of care by allowing providers online
Accepted 15 May 2015
access to healthcare information generated by other providers at the point of care. However, evidence concerning the effectiveness of the technology is limited hindering the wide
Keywords:
adoption of a HIE. The objective of this study was to assess impacts of a HIE on healthcare
Community networks
utilization and costs of patient episodes at a tertiary care hospital following referrals by
Electronic health records
clinic physicians.
Health information exchange
Material/methods: We studied 1265 HIE and 2702 non-HIE episodes after physicians referred
Health information technology
patients from 35 HIE and 59 non-HIE clinics to Seoul National University Bundang Hospital
Healthcare cost
(SNUBH) during a 17-month period from June 2009. We examined 9 measures of healthcare utilization and the magnitude of clinical information exchanged in 4 categories. We estimated the savings resulting from HIE use through linear regression models with dummy variables for HIE participation and patient classification codes controlling the case-mix differences between HIE and non-HIE cases.
Abbreviations: EMR, electronic medical record; HIE, health information exchange; KDRG, Korean diagnosis related group; KOPG, Korean outpatient group; KRW, Korean won; NHIS, National Health Insurance Service of Korea; SNUBH, Seoul National University Bundang Hospital; USD, US dollar. ∗ Corresponding author. Tel.: +82 10 5235 0903; fax: +82 31 787 4054. E-mail addresses: [email protected] (H. Park), [email protected] (S.-i. Lee), [email protected] (H. Hwang), [email protected] (Y. Kim), [email protected] (E.-Y. Heo), [email protected] (J.-W. Kim), [email protected] (K. Ha). http://dx.doi.org/10.1016/j.ijmedinf.2015.05.008 1386-5056/© 2015 Elsevier Ireland Ltd. All rights reserved.
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Results: The total charges incurred by the HIE group during episodes at SNUBH were approximately 13% lower (P < 0.001), and the charges for clinical laboratory tests, pathological diagnosis, function tests, and diagnostic imaging were 54% (P < 0.001), 76% (P < 0.001), 73% (P < 0.001), and 80% (P < 0.001) lower for the HIE group than for the non-HIE group. SNUBH physicians had access to more clinical information for HIE than for non-HIE patients. Conclusions: HIE technology improved physicians’ access to past clinical information, which appeared to reduce diagnostic test utilization and healthcare costs. The payer was the major beneficiary of HIE cost savings whereas providers paid for the technology. Fair allocation of benefits and costs among stakeholders is needed for wide HIE adoption. © 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
The adoption of a health information exchange (HIE), which is defined as the electronic transmission of healthcare information among healthcare providers, has been slow despite its highly anticipated benefits in healthcare quality and cost [1–3]. The technology enables provider online access to healthcare information generated by others at the point of care, and therefore it is expected to improve the quality and efficiency of care and reduce the operating and administrative costs of healthcare providers [4]. South Korea, in particular, needs this technology because care is fragmented. Hospitals employ their own medical staff and are closed to physicians at local clinics. However, the barriers to technology adoption are particularly high. Hospitals and clinics often compete for patients, with a large share of hospital revenue coming from outpatient care. Further complicating HIE adoption, providers are paid on a fee-for-service basis such that higher utilization of healthcare services generates higher payments for providers. As a result, providers’ financial incentives are not aligned with containment of healthcare costs through the adoption of an HIE. Previous literature has emphasized the importance of effectiveness research for wide adoption and diffusion of an HIE, particularly its value in saving healthcare costs [2,5–8]. Financial incentives that align interests of stakeholders cannot be designed without proper estimation of benefits, which previous studies have indicated as a significant factor in facilitating the adoption and sustainability of the adopted technology [4,9–12]. However, few researchers have attempted to measure the economic benefits of an HIE, and evidence quantified with empirical data obtained from an operational HIE was sketchy [13–18]. Overhage et al. found a decrease of 26 US dollars (USD) per emergency department encounter in an HIE group at 1 of 2 pilot study sites in Indianapolis, Indiana, but no significant savings in the other site [13]. Frisse et al. found that HIE access was significantly associated with a decrease in hospital admissions and utilization of head and body computed tomography as well as laboratory testing in a study of emergency department encounters in Memphis, Tennessee [16]. Magnus et al. [17] and Bell et al. [18] reported improvements in quality of care measures through the HIE technology in HIV care settings. Further studies are needed to strengthen the evidence of HIE technology impact on healthcare cost and quality.
We examined physicians’ acceptance and use of an HIE, patients’ perceptions of the technology, and the costs and benefits of the system as part of a 3-year pilot project supported by a grant from the Ministry of Health and Welfare of South Korea [19–21]. In this report of the study, we assessed the impact of an HIE on healthcare utilization and costs. We estimated cost savings by comparing healthcare utilization of 2 groups of patients receiving similar care but who differed in terms of access to HIE technology.
2.
Materials and methods
2.1.
Study setting
The Ministry of Health and Welfare of South Korea funded a 3-year pilot project to examine the feasibility of using an HIE in South Korea, operate a prototype system, obtain evidence on the clinical and economic impacts of the technology, and explore other issues that may emerge when an HIE is introduced. Seoul National University Bundang Hospital (SNUBH), a 980-bed tertiary care university teaching hospital located 20 km south of Seoul, received a grant from the ministry and launched the pilot project in November 2007. The first version of the system was deployed in June 2008 and was completed in October 2009. Terms and conditions of participation were presented to local clinics and physician practices (hereafter, clinics) with referral arrangements with the hospital, either in recruitment sessions or in visits to clinics on their request. Clinic participation in the project was on a voluntary basis, and 35 clinics participated in the project as of October 2009. SNUBH and participating clinics had been using electronic medical records (EMRs) at the time the project commenced. The HIE system was based on a federated architecture model, and in the final system, exchanged information included patients’ demographic data and health status, including diagnoses with chief complaints, prescribed medications, laboratory results, diagnostic images, duration and content of treatments, care plans, vital signs, history, and summaries [19,20]. Physicians at HIE clinics introduce the HIE system to patients being transferred to SNUBH and ask them whether they would participate in the system. Patients consent by signing with a pen and pad designed for this purpose, then the referral message is sent to the central registry server and the registry at SNUBH. Upon their first visit to SNUBH,
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patients register their visit at the office of referrals and an office staff member enters the patients’ visit into the hospital’s EMR system as per the procedure for all patients. The central registry server checks information from the clinic and against that entered by the hospital, then patient care information that had been entered by the clinic is retrieved for physicians’ review. When hospital physicians first see HIE patients in their office, the system flashes a button on a display screen signaling that the patient is an HIE participant. Physicians click the button and patient care information from the clinic and sourced through the HIE is shown to the physicians through the hospital’s EMR system. The system log confirmed that physicians click the button at over 99% of first encounters to see patients’ care information exchanged in the HIE system.
2.2.
Study design and analytical model
Patients receiving care for acute or chronic conditions at a clinic with referral arrangements with SNUBH may be sent to SNUBH upon their own request or when a clinic physician deems the need for tertiary care. A patient’s care at the hospital is either completed at SNUBH or he/she is referred back to the clinic for routine care when the tertiary care ends. Hospitals in South Korea employ their own physicians and are closed to physicians employed at outside clinics, typically resulting in disconnected care experiences for patients seeking medical attention at both clinics and hospitals. In the conventional system, referring physicians issue a letter, delivered by the patient, that typically contains little information about patients’ care at the clinic, and physicians at clinics do not have access to care information logged at the hospital even after a patient is referred back to them. When a patient deems the need for the full exchange of care information generated at the clinic, he/she asks the clinic to copy medical records and/or diagnostic imaging films, pays fees for the service, and delivers copied information to the hospital. Through the HIE system, the clinician’s letter is transmitted online to the hospital with relevant patient care information, at the clinic. Under the HIE, physicians at the referring clinics can subsequently access the referred patients’ care information entered by SNUBH physicians. However, this aspect of the HIE which has been addressed in Lee et al. [20] as to physicians’ perceptions of the HIE is not included in this paper. In this study, which was approved by the Institutional Review Board of SNUBH, we examined resource utilization during episodes of care at SNUBH. An episode of care starts when a referred patient visits the hospital, and it ends when the care is completed at the hospital or when the patient is referred back to the referring clinic. An episode of care consists of outpatient visits with or without hospitalizations. We used patient classifications to consolidate episodes into groups with homogenous resource-utilization profiles. We classified episodes with hospitalizations using Korean Diagnosis Related Groups (KDRGs), an inpatient classification system similar to the Diagnosis Related Groups used in the United States, and classified outpatient episodes without hospitalizations using Korean Outpatient Groups (KOPGs), which is similar to the Ambulatory Patient Groups used in the United States [22–24]. We used the first 4-digits of the 6-digit classification codes of the KDRGs and KOPGs in this study to
avoid instability in statistical estimations caused by small cell sizes, which collapses age categories as well as complication and comorbidity categories in the classification process. We assumed that resources needed to treat patients’ conditions are homogeneous within a classification code regardless of the patients’ HIE participation status. We assigned a KDRG or KOPG code to each episode and used the codes in the analytical model to control for the difference in the case mixes of the HIE and non-HIE groups. We used a multivariate analysis of variance (MANOVA) model for unbalanced data to estimate the effects of the HIE system on resource utilization incurred during an episode of care at SNUBH following referrals by physicians at local clinics controlling for the difference in the case mixes of the HIE and non-HIE groups, which needs to be analyzed with a linear regression model: Yi = ˛ + ˇHIEi +
j PGij + εi
j
in which i = subscript for episodes; j = subscript for patient groups; Y = log-transformed measure of resource utilization; HIE = 1 if the episode is in the HIE group and 0 otherwise; PGj = 1 if the episode is associated with the jth patient group and 0 otherwise; ˇ, j = coefficients; ε = error term. We log-transformed the dependent variables, and the percentage difference of a resource utilization measure between the HIE and the non-HIE groups was derived with the estimate of the ˇ coefficient: 100 × (eˇ¨ − 1). In addition to resource utilization, we also examined the magnitude of information transmitted to SNUBH from referring clinics. We computed descriptive statistics of the magnitude of information transmitted to SNUBH from referring clinics as well as the measures of resource utilization, and we tested the statistical significance of the differences between the HIE and non-HIE groups with the Wilcoxon ranksum test.
2.3.
Study subjects and data
The initial HIE group included all episodes referred to SNUBH from 35 HIE clinics in which treatment was started at the hospital from June 2009 through October 2010. The non-HIE group included those cases referred by 59 non-HIE clinics (Fig. 1). We assigned KDRG and KOPG codes to each episode, and retained those coded groups that contained 2 or more episodes in each of the HIE and non-HIE groups: 100 KOPGs and 29 KDRGs. The final study dataset included a total of 1265 HIE episodes and 2702 non-HIE episodes. The sizes of the 35 HIE clinics measured by the number of practicing physicians ranged from 1 to 5 with a mean of 1.86, and the sizes of the 59 non-HIE clinics ranged from 1 to 14 with a mean of 1.81; the means were not significantly different. The 3 most frequent specialties among both HIE and non-HIE clinics were internal medicine (34%, 18%), otorhinolaryngology (12%, 16%), and ophthalmology (12%, 14%). Table 1 presents general characteristics of study subjects. The average age, the gender of patients and the type of episode among HIE and non-HIE groups did not significantly differ. Approximately 89% of episodes in this study reflected cases
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Fig. 1 – Study subjects.
consisting of only outpatient care. The 3 most frequently assigned KOPGs among HIE episodes without hospitalizations reflect minor ophthalmological tests and procedures (6.7%), symptoms and signs involving the circulatory and respiratory systems (4.8%), and endoscopy of the upper airway (4%). Similar symptoms were among the most treated in the non-HIE episodes: minor ophthalmological tests and procedures (7.3%), superficial needle biopsy (7%), and otorhinolaryngologic function tests (6%). The 3 most frequently assigned KDRGs among HIE episodes with hospitalizations were lens procedures with large incisions (10.7%), inguinal and femoral hernia procedures without resection of intestine (7.1%), and major thyroid procedures (6.4%). Among non-HIE episodes, they included major thyroid procedures (9.7%), gastroscopy for non-major digestive disease (8.4%), and major retinal and vitreous procedures without lens procedures (6.5%). We studied 9 measures of resource utilization incurred during an episode of care at SNUBH: total charges; costs for medication as well as clinical laboratory, pathological
diagnostic, function, and diagnostic imaging tests; numbers of orders, outpatient visits, and inpatient days. The entire population of South Korea is covered either by the National Health Insurance Program or by the Medical Aid Program, which are both administered by the National Health Insurance Service (NHIS). A fee schedule for each calendar year is set by the NHIS, and we computed charges based on the fee schedule of the year 2009. Charges included both physician and hospital fees, both insurer and patient payments for covered services, and patient payment for non-covered services. Charge data were extracted from the hospital accounting system and data for the number of orders, outpatient visits, and inpatient days were extracted from EMRs using computer programs created for this study. We estimated 9 models, one for each measure, to examine the effects of the HIE technology on utilization of different types of resources. We counted the number of information items in 4 categories: prescription of medication, order and results of clinical laboratory tests, order and results of diagnostic imaging
Table 1 – General characteristics of study subjects. HIE group
Non-HIE group
Characteristic
(n = 1265)
(n = 2702)
Mean age in years (SD) Gender (%) Male Female Type of episode (%) W/o hospitalization (outpatient visits only) W/hospitalization (outpatient and inpatient care)
43.4 (25.1)
44.2 (24.5)
0.65a
611 (48%) 654 (52%)
1237 (46%) 1465 (54%)
0.14b
1125 (89%) 140 (11%)
2381 (89%) 321 (11%)
0.46b
a b
Wilcoxon test. Pearson’s chi-square test.
P-value
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Table 2 – Descriptive statistics and comparison of group means of the study variables for the health information exchange (HIE) and non-HIE groups. HIE group Variable
Mean
Episodes w/o hospitalization (N for HIE group = 1125, for non-HIE group = 2381) 244,049 Total chargesb 6026 Charges for drugb 5072 Charges for clinical pathology testsb 38,112 Charges for pathological diagnosisb 63,728 Charges for function testsb 95,238 Charges for diagnostic imagingb Num. of orders 6.30 Num. of outpatient visits 1.90 Num. of info. items exchanged: drug 1.65 Num. of info. items exchanged: clinical laboratory tests 2.16 Num. of info. items exchanged: diagnostic imaging 0.01 Num. of info. items exchanged: treatment procedures 0.06 Episodes w/ hospitalization (N for HIE group = 140, for non-HIE group = 321) 2123,910 Total chargesb 138,863 Charges for drugb 92,408 Charges for clinical pathology testsb 64,624 Charges for pathologicaldiagnosisb 148,478 Charges for function testsb 85,611 Charges for diagnostic imagingb Num. of orders 53.35 Num. of outpatient visits 4.10 Length of hospital stay 3.21 Num. of info. items exchanged: drug 1.24 Num. of info. items exchanged: clinical laboratory tests 2.34 Num. of info. items exchanged: diagnostic imaging 0.03 Num. of info. items exchanged: treatment procedures 0.05 a b
P-valuea
SD
Mean
SD
281,053 66,462 18,053 62,899 105,601 207,474 6.66 0.72 5.86 7.17 0.14 0.24
274,622 7683 7418 42,059 70,165 107,540 7.00 1.89 0.18 0.95 0.02 0.02
293,267 75,510 21,537 75,045 110,019 204,890 7.13 0.68 0.75 4.69 0.05 0.15
<0.001 0.16 0.003 0.98 0.06 0.015 <0.001 0.95 <0.001 0.03 0.47 <0.001
2809,208 204,518 208,816 128,667 502,387 256,850 50.27 1.37 3.06 2.73 5.95 0.21 0.22
2656,634 152,301 166,638 139,860 186,474 141,426 61.48 3.38 3.90 0.14 1.74 0.05 0.02
2865,746 164,110 199,943 137,457 434,875 275,319 42.51 1.44 3.19 0.60 7.05 0.24 0.16
0.002 0.73 <0.001 <0.001 <0.001 <0.001 0.04 <0.001 0.09 <0.001 0.13 0.48 0.03
Wilcoxon test. Unit = Korean Won (1 US Dollar = 1168 Korean Won as of December 31, 2009).
tests, and order of treatment procedures. Data on HIE-group information exchanges were extracted from the HIE system using a computer program written for this study, and using the identical logic used to create the data-extracting computer program for the HIE database, we manually extracted data for the non-HIE group from referral letters issued by clinic physicians and medical records and imaging films supplied by patients. About 28% of patients in the non-HIE group brought copies of medical records and/or imaging films to the hospital, and medical records and imaging films are scanned and uploaded to the hospital’s EMR system by a staff member of the office of referrals at the time of registration. A reviewer performed the entire extraction of data for the nonHIE group and another reviewer went over the data extraction and made notes when she found errors or discrepancies. The first reviewer subsequently examined the notes and finalized the data extraction.
3.
Non-HIE group
Results
3.1. Descriptive statistics and comparison of group means Without controlling for the differences in the case mixes of episodes in the HIE and non-HIE groups, we found that the mean total charges and the mean number of orders
were significantly lower in the HIE group compare to the non-HIE group: the mean for episodes involving only outpatient services was 244,049 KRW in the HIE group whereas the mean was 274,622 KRW in the non-HIE group (P < 0.001), and the mean total charges for episodes with hospitalization was 2123,910 KRW in the HIE group whereas the mean was 2656,634 KRW in the non-HIE group (P = 0.002) (Table 2). The mean charges for various types of resources we studied, except for medication and pathological diagnosis for episodes involving only outpatient services and medication for those with hospitalizations, were significantly different between the two groups. For episodes with hospitalizations, the mean number of outpatient visits was significantly lower in the non-HIE group than in the HIE group (4.1 and 3.38 for the HIE and non-HIE groups, respectively; P < 0.001) whereas the mean length of hospital stay was shorter in the HIE group than in the non-HIE group (3.21 and 3.90 for the HIE and non-HIE groups, respectively; P = 0.09). We found physicians at SNUBH possessed more information about the care given at the referring clinics when they treated patients referred from HIE clinics than when they treated patients from non-HIE clinics. The mean numbers of information items transmitted to SNUBH were higher in the HIE group for the types of information studied, particularly for medication and treatment procedures, regardless of whether
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Table 3 – Effect of using health information exchange (HIE) on charges and utilization as estimated with the regression models (N = 3967). Dependent variable
Model r-square (%)
Total charges Total charges for drug Total charges for clinical laboratory tests Total charges for pathological diagnosis Total charges for function tests Total charges for diagnostic imaging Num. of orders Num. of outpatient visits Length of hospital staya a
Coefficient estimate of the HIE dummy variable (ˇ)
49 61 54 31 39 31 20 35 80
P-value of the estimate
−0.14 −0.20 −0.77 −1.41 −1.30 −1.62 −1.01 0.02 −0.06
<0.001 0.33 <0.001 <0.001 <0.001 <0.001 <0.001 0.13 0.16
% Increase or decrease compare to non-HIE group (%) −13 −18 −54 −76 −73 −80 −63 2 −6
The model was analyzed with 461 episodes that had inpatient care.
the patient was hospitalized or only received outpatient care. The mean number of information items as to medication was 1.65 for episodes without hospitalization in the HIE group whereas the mean was 0.18 in the non-HIE group, and the mean for episodes with hospitalization was 1.24 in the HIE group whereas the mean was 0.14 in the non-HIE group.
3.2.
Effect of HIE on resource utilization
The R2 values of the regression models with the HIE and patient-group dummy variables were modestly high for all 9 models: They ranged from 20% (number of orders) to 80% (length of hospital stay) (Table 3). The total charges incurred during an episode of care at SNUBH for patients referred by clinic physicians were approximately 13% lower for the HIE group than for the non-HIE group (estimated after controlling for the difference in case mixes of patients in the two groups): P < 0.001. Similarly, 63% fewer orders were prescribed during an episode categorized in the HIE group (P < 0.001) than in the non-HIE group. Total charges for 4 types of diagnostic tests – clinical laboratory, pathological diagnosis, function, and imaging – were significantly lower in the HIE group, and the percentage difference ranged from 54% (clinical laboratory tests) to 80% (diagnostic imaging). Although the total charges for medications were lower for those in the HIE group, the difference was not statistically significant. Likewise, the length of hospital stay for cases categorized as HIE was less than for those in the non-HIE group, but the difference was not statistically significant (6%, P = 0.16). The greater number of outpatient visits by HIE users showed a small and statistically insignificant difference over that for the non-HIE group (2%, P = 0.13).
4.
Discussion
4.1.
Principal results
that of patients referred by physicians at non-participating clinics. To control for differences in disease types of cases in the 2 groups, we used patient classification codes in linear regression models. Study findings empirically evidenced savings in healthcare costs and showed the potential of an HIE to improve quality of care as well. Total charges and charges for diagnostic tests were lower in the HIE group than in the nonHIE group as hypothesized and predicted in previous studies [2,10,25–27] and the total cost savings per episode under an HIE, as estimated in this study, was 13%. Further, physicians at SNUBH had better access to information about care given to patients from referring clinics. The number of orders prescribed during an episode of care at SNUBH was significantly fewer with the use of the HIE technology, and commensurate cost savings in diagnostic tests appeared firm and significant. The percentage reduction in charges for the 4 types of diagnostic tests studied ranged from 54% to 80%. We confirmed in the examination of the system log that physicians at SNUBH almost always look at patients’ care information exchanged in the HIE system. In a previous study [20], we reported that the most needed and valued information indicated by physicians related to pathology, laboratory, and diagnostic imaging along with medication and working diagnoses. The empirical findings we report in this study confirm the subjective perceptions of physicians that we had previously measured; however, physician agreement about the potential benefits of cost savings was relative low compared to their agreement about the potential benefit of HIEs in terms of quality. We found costs for medications were lower in the HIE than in the non-HIE group, but the difference was not significant. Care given at SNUBH was inherently different from that provided at referring clinics (the very reason patients were referred to SNUBH from local clinics), and this treatment incomparability may explain the lack of differences in the costs of medication.
4.2.
In this study, we quantitatively assessed the potential of HIEs to contain healthcare costs. We compared resource utilization at a tertiary care hospital of patients referred by physicians from local clinics participating in the HIE pilot program to
Limitations
The study findings should be interpreted within the context of the study design and limitations. First, in this study, we only examined episodes of tertiary care based on referrals to a hospital from local clinics. Future studies should explore empirical evidence on the effects of the HIE
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technology in other types of episodes that involve care with multiple providers. Second, savings of healthcare costs in this study could be underestimated because the scope of the study only included care delivered at SNUBH; episodes of care for patients sent back to referring clinics were not included. In a previously published study [20], we found that physicians in clinics were more likely to find useful information in the HIE system than their counterparts do at the tertiary care hospital, and the savings potential could be larger when cases referred back to the clinics are considered. Further, study results did not include savings in administrative and clerical costs of healthcare providers such as copying and scanning medical records, uploading them to the EMR system, and mailing or e-mailing health information to other providers. Third, we only examined charges and did not attempt to measure and monetize benefits in the quality domain, which could result in underestimation of beneficial outcomes of the HIE. According to the results of both physician and patient surveys, participants’ appreciation about the quality benefits associated with the technology were higher than they were concerning the benefits of cost savings [20,21]. Fourth, workflow at SNUBH was established when the EMR system was rolled out in 2004, and no significant changes were made to it with the implementation of the HIE. Previous studies indicated that workflow would significantly influence the impact of the technology, and we cannot make an assumption on how workflow issues have contributed to our findings [10,12,13,28]. Fifth, caution should be exercised with regard to the generalizability of study findings. The payment is based on a fee-for-service mechanism, and policy initiatives to contain healthcare costs are unsubstantial in South Korea. Further, due to poor financial incentives from increases in revenue stemming from the salary structure and the public ownership of their facility, SNUBH physicians feel less pressured than their counterparts at other hospitals and clinics to increase revenue. Lastly, the study may not be free from selection biases, particularly the bias in quality between the HIE and non-HIE clinics. Although sizes of HIE and non-HIE clinics were similar, we did not have access to patient care information at non-HIE clinics and could not determine whether the quality of care at those non-HIE clinics were comparable to the quality provided at HIE clinics. Further, the difference in the case mixes of the HIE and non-HIE groups may not have been addressed adequately in the analytical models because of the collapses of age and complication and comorbidity categories. There were no reported cases of patients’ opting out of the HIE group; therefore, the patients’ selection bias within the HIE group is not of concern.
5.
Conclusions
In this study, we showed HIE technology improved physicians’ access to clinical information at referring clinics, which appeared to reduce diagnostic test utilization and healthcare costs. However, substantial re-alignment of providers’ incentives must be followed to encourage widespread adoption
of the technology and the realization of the commensurate benefits of it, particularly in South Korea due to the fee-for-service payment mechanism. Among critical factors for successful adoption of the HIE technology as suggested in previous literature, the need for fair allocation of benefits and costs among stakeholders was substantiated in this study [4,9,11,12,29]. The major beneficiary of the cost savings shown in this study was the payer, who may need to subsidize providers’ investment in the technology and/or share savings with them. Although we did not report in this study, we found savings in the hospital’s administrative and clerical costs and in physicians’ time at SNUBH and the magnitude of the savings was about 30% of the payer’s savings. We reported in the previous study that SNUBH physicians expressed their concern about the financial burden that comes with the technology [20]. Although physicians appeared less concerned about provider risk, providers may lose revenue with an HIE in a fee-for-service based payment system [20]. The financial benefits to patients are limited because they are responsible only for the coinsurance portion of healthcare costs for covered services and for expenses of non-covered services. The actual amount of savings for 89% of individual episodes, which consisted of outpatient visits only, accumulated to 35,700 Korean Won (KRW, 31 USD) with the mean total charges for the non-HIE group (Table 2) coming to 274,622 KRW (235 USD). The savings for patients came to approximately 16,065 KRW (14 USD) with 45% coinsurance imposed by the NHIS for outpatient visits to tertiary care hospitals. We had reported that patients’ perceptions reflect the lack of impact exerted by such a small savings but we also saw that patients were enthusiastic about the technology, not because of its potential for a reduced burden of healthcare costs, but because of the convenience and quality of care they experienced with the technology [21]. Despite lack of physician or patient enthusiasm for HIE costs savings, the magnitude of savings would be significant for the insurer, NHIS, across multiple provider settings. A study undertaken in Massachusetts estimated that 57% of all acute care visits involved care at multiple hospitals [30]. Multifaceted initiatives to contain healthcare costs and to improve healthcare quality through payment reform and efforts to align stakeholder incentives are needed for wide adoption of an HIE and full realization of the technology benefits.
Authors’ contribution Hayoung Park, PhD conceived and designed the study, analyzed data, interpreted findings, and drafted the article. Sang-il Lee, MD PhD conceived and designed the study, interpreted findings, and drafted the article. Yoon Kim, MD PhD reviewed the study design and interpretation of study findings as well as drafted the article. Eun-Young Heo, MS collected data, assured data quality, and interpreted data as well as drafted the article. Hee Hwang, MD PhD and Jeong-Whun Kim, MD PhD reviewed the study design and interpretation of study findings as well as drafted the article. Kyooseob Ha, MD PhD conceived and designed the study, interpreted study findings,
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Summary points What was already known on the topic: [5]
• The HIE technology is expected to improve the quality and efficiency of care at the same time mainly based on conceptual hypotheses; empirical evidence with quantitative data from an operational HIE is sketchy. • Studies reported savings of healthcare cost and reduced utilization of healthcare at emergency departments. What this study added to our knowledge: • Quantified savings of healthcare costs where patients are referred by physicians at community clinics to a tertiary hospital for further complicated care. • Sources of savings included clinical laboratory tests, pathological diagnosis, function tests, and diagnostic imaging, but were not seen in drugs, outpatient visits and hospital stays.
drafted the article, and directed the pilot program as well. All the authors revised the manuscript critically for important scholarly content, and provided final approval of the version submitted.
[6]
[7]
[8]
[9]
[10]
[11]
[12]
Competing interests None.
[13]
Acknowledgements This study was funded by a grant from the Korea Healthcare Technology R&D Project (A050909) and was partially supported by a grant from the Korea Healthcare Technology R&D Project (A112067) of the Ministry of Health and Welfare of the Republic of Korea.
references
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[26] A.L. Hincapie, T.L. Warholak, A.C. Murcko, et al., Physicians’ opinions of a health information exchange, J. Am. Med. Inform. Assoc. 18 (2011) 60–65 [PMID: 21106994]. [27] A. Wright, C. Soran, C.A. Jenter, et al., Physician attitudes toward health information exchange: results of a statewide survey, J. Am. Med. Inform. Assoc. 17 (2010) 66–70 [PMID: 20064804]. [28] K.M. Unertl, K.B. Johnson, N.M. Lorenzi, Health information exchange technology on the front lines of healthcare: workflow factors and patterns of use, J. Am. Med. Inform. Assoc. 19 (3) (2012) 392–400 [PMID: 22003156]. [29] P. Fontaine, S.E. Ross, T. Zink, et al., Systematic review of health information exchange in primary care practices, J. Am. Board. Fam. Med. 23 (5) (2010) 655–670 [PMID: 20823361]. [30] F.C. Bourgeois, K.L. Olson, K.D. Mandl, Patients treated at multiple acute health care facilities: quantifying information fragmentation, Arch. Intern. Med. 170 (22) (2010) 1989–1995 [PMID: 21149756].
journal homepage: www.ijmijournal.com
Can a health information exchange save healthcare costs? Evidence from a pilot program in South Korea Hayoung Park a , Sang-il Lee b , Hee Hwang c,∗ , Yoon Kim d , Eun-Young Heo e , Jeong-Whun Kim f , Kyooseob Ha g a
Technology Management, Economics, and Policy Graduate Program, Seoul National University, 1 Kwanak-ro, Kwanak-gu, Seoul 151-015, Republic of Korea b Department of Preventive Medicine, College of Medicine, University of Ulsan, 86 Asan Byungwon-gil, Songpa-gu, Seoul 138-736, Republic of Korea c Department of Pediatrics, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea d Department of Health Policy and Management, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul 110-799, Republic of Korea e Department of Medical Informatics, Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea f Department of Otorhinolaryngology, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea g Department of Psychiatry, College of Medicine, Seoul National University and Seoul National University Bundang Hospital, 82 Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si 463-707, Republic of Korea
a r t i c l e
i n f o
a b s t r a c t
Article history:
Objective: Governments and institutions across the world have made efforts to adopt and
Received 20 January 2015
diffuse the health information exchange (HIE) technology with the expectation that the
Received in revised form 6 May 2015
technology would improve the quality and efficiency of care by allowing providers online
Accepted 15 May 2015
access to healthcare information generated by other providers at the point of care. However, evidence concerning the effectiveness of the technology is limited hindering the wide
Keywords:
adoption of a HIE. The objective of this study was to assess impacts of a HIE on healthcare
Community networks
utilization and costs of patient episodes at a tertiary care hospital following referrals by
Electronic health records
clinic physicians.
Health information exchange
Material/methods: We studied 1265 HIE and 2702 non-HIE episodes after physicians referred
Health information technology
patients from 35 HIE and 59 non-HIE clinics to Seoul National University Bundang Hospital
Healthcare cost
(SNUBH) during a 17-month period from June 2009. We examined 9 measures of healthcare utilization and the magnitude of clinical information exchanged in 4 categories. We estimated the savings resulting from HIE use through linear regression models with dummy variables for HIE participation and patient classification codes controlling the case-mix differences between HIE and non-HIE cases.
Abbreviations: EMR, electronic medical record; HIE, health information exchange; KDRG, Korean diagnosis related group; KOPG, Korean outpatient group; KRW, Korean won; NHIS, National Health Insurance Service of Korea; SNUBH, Seoul National University Bundang Hospital; USD, US dollar. ∗ Corresponding author. Tel.: +82 10 5235 0903; fax: +82 31 787 4054. E-mail addresses: [email protected] (H. Park), [email protected] (S.-i. Lee), [email protected] (H. Hwang), [email protected] (Y. Kim), [email protected] (E.-Y. Heo), [email protected] (J.-W. Kim), [email protected] (K. Ha). http://dx.doi.org/10.1016/j.ijmedinf.2015.05.008 1386-5056/© 2015 Elsevier Ireland Ltd. All rights reserved.
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Results: The total charges incurred by the HIE group during episodes at SNUBH were approximately 13% lower (P < 0.001), and the charges for clinical laboratory tests, pathological diagnosis, function tests, and diagnostic imaging were 54% (P < 0.001), 76% (P < 0.001), 73% (P < 0.001), and 80% (P < 0.001) lower for the HIE group than for the non-HIE group. SNUBH physicians had access to more clinical information for HIE than for non-HIE patients. Conclusions: HIE technology improved physicians’ access to past clinical information, which appeared to reduce diagnostic test utilization and healthcare costs. The payer was the major beneficiary of HIE cost savings whereas providers paid for the technology. Fair allocation of benefits and costs among stakeholders is needed for wide HIE adoption. © 2015 Elsevier Ireland Ltd. All rights reserved.
1.
Introduction
The adoption of a health information exchange (HIE), which is defined as the electronic transmission of healthcare information among healthcare providers, has been slow despite its highly anticipated benefits in healthcare quality and cost [1–3]. The technology enables provider online access to healthcare information generated by others at the point of care, and therefore it is expected to improve the quality and efficiency of care and reduce the operating and administrative costs of healthcare providers [4]. South Korea, in particular, needs this technology because care is fragmented. Hospitals employ their own medical staff and are closed to physicians at local clinics. However, the barriers to technology adoption are particularly high. Hospitals and clinics often compete for patients, with a large share of hospital revenue coming from outpatient care. Further complicating HIE adoption, providers are paid on a fee-for-service basis such that higher utilization of healthcare services generates higher payments for providers. As a result, providers’ financial incentives are not aligned with containment of healthcare costs through the adoption of an HIE. Previous literature has emphasized the importance of effectiveness research for wide adoption and diffusion of an HIE, particularly its value in saving healthcare costs [2,5–8]. Financial incentives that align interests of stakeholders cannot be designed without proper estimation of benefits, which previous studies have indicated as a significant factor in facilitating the adoption and sustainability of the adopted technology [4,9–12]. However, few researchers have attempted to measure the economic benefits of an HIE, and evidence quantified with empirical data obtained from an operational HIE was sketchy [13–18]. Overhage et al. found a decrease of 26 US dollars (USD) per emergency department encounter in an HIE group at 1 of 2 pilot study sites in Indianapolis, Indiana, but no significant savings in the other site [13]. Frisse et al. found that HIE access was significantly associated with a decrease in hospital admissions and utilization of head and body computed tomography as well as laboratory testing in a study of emergency department encounters in Memphis, Tennessee [16]. Magnus et al. [17] and Bell et al. [18] reported improvements in quality of care measures through the HIE technology in HIV care settings. Further studies are needed to strengthen the evidence of HIE technology impact on healthcare cost and quality.
We examined physicians’ acceptance and use of an HIE, patients’ perceptions of the technology, and the costs and benefits of the system as part of a 3-year pilot project supported by a grant from the Ministry of Health and Welfare of South Korea [19–21]. In this report of the study, we assessed the impact of an HIE on healthcare utilization and costs. We estimated cost savings by comparing healthcare utilization of 2 groups of patients receiving similar care but who differed in terms of access to HIE technology.
2.
Materials and methods
2.1.
Study setting
The Ministry of Health and Welfare of South Korea funded a 3-year pilot project to examine the feasibility of using an HIE in South Korea, operate a prototype system, obtain evidence on the clinical and economic impacts of the technology, and explore other issues that may emerge when an HIE is introduced. Seoul National University Bundang Hospital (SNUBH), a 980-bed tertiary care university teaching hospital located 20 km south of Seoul, received a grant from the ministry and launched the pilot project in November 2007. The first version of the system was deployed in June 2008 and was completed in October 2009. Terms and conditions of participation were presented to local clinics and physician practices (hereafter, clinics) with referral arrangements with the hospital, either in recruitment sessions or in visits to clinics on their request. Clinic participation in the project was on a voluntary basis, and 35 clinics participated in the project as of October 2009. SNUBH and participating clinics had been using electronic medical records (EMRs) at the time the project commenced. The HIE system was based on a federated architecture model, and in the final system, exchanged information included patients’ demographic data and health status, including diagnoses with chief complaints, prescribed medications, laboratory results, diagnostic images, duration and content of treatments, care plans, vital signs, history, and summaries [19,20]. Physicians at HIE clinics introduce the HIE system to patients being transferred to SNUBH and ask them whether they would participate in the system. Patients consent by signing with a pen and pad designed for this purpose, then the referral message is sent to the central registry server and the registry at SNUBH. Upon their first visit to SNUBH,
660
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patients register their visit at the office of referrals and an office staff member enters the patients’ visit into the hospital’s EMR system as per the procedure for all patients. The central registry server checks information from the clinic and against that entered by the hospital, then patient care information that had been entered by the clinic is retrieved for physicians’ review. When hospital physicians first see HIE patients in their office, the system flashes a button on a display screen signaling that the patient is an HIE participant. Physicians click the button and patient care information from the clinic and sourced through the HIE is shown to the physicians through the hospital’s EMR system. The system log confirmed that physicians click the button at over 99% of first encounters to see patients’ care information exchanged in the HIE system.
2.2.
Study design and analytical model
Patients receiving care for acute or chronic conditions at a clinic with referral arrangements with SNUBH may be sent to SNUBH upon their own request or when a clinic physician deems the need for tertiary care. A patient’s care at the hospital is either completed at SNUBH or he/she is referred back to the clinic for routine care when the tertiary care ends. Hospitals in South Korea employ their own physicians and are closed to physicians employed at outside clinics, typically resulting in disconnected care experiences for patients seeking medical attention at both clinics and hospitals. In the conventional system, referring physicians issue a letter, delivered by the patient, that typically contains little information about patients’ care at the clinic, and physicians at clinics do not have access to care information logged at the hospital even after a patient is referred back to them. When a patient deems the need for the full exchange of care information generated at the clinic, he/she asks the clinic to copy medical records and/or diagnostic imaging films, pays fees for the service, and delivers copied information to the hospital. Through the HIE system, the clinician’s letter is transmitted online to the hospital with relevant patient care information, at the clinic. Under the HIE, physicians at the referring clinics can subsequently access the referred patients’ care information entered by SNUBH physicians. However, this aspect of the HIE which has been addressed in Lee et al. [20] as to physicians’ perceptions of the HIE is not included in this paper. In this study, which was approved by the Institutional Review Board of SNUBH, we examined resource utilization during episodes of care at SNUBH. An episode of care starts when a referred patient visits the hospital, and it ends when the care is completed at the hospital or when the patient is referred back to the referring clinic. An episode of care consists of outpatient visits with or without hospitalizations. We used patient classifications to consolidate episodes into groups with homogenous resource-utilization profiles. We classified episodes with hospitalizations using Korean Diagnosis Related Groups (KDRGs), an inpatient classification system similar to the Diagnosis Related Groups used in the United States, and classified outpatient episodes without hospitalizations using Korean Outpatient Groups (KOPGs), which is similar to the Ambulatory Patient Groups used in the United States [22–24]. We used the first 4-digits of the 6-digit classification codes of the KDRGs and KOPGs in this study to
avoid instability in statistical estimations caused by small cell sizes, which collapses age categories as well as complication and comorbidity categories in the classification process. We assumed that resources needed to treat patients’ conditions are homogeneous within a classification code regardless of the patients’ HIE participation status. We assigned a KDRG or KOPG code to each episode and used the codes in the analytical model to control for the difference in the case mixes of the HIE and non-HIE groups. We used a multivariate analysis of variance (MANOVA) model for unbalanced data to estimate the effects of the HIE system on resource utilization incurred during an episode of care at SNUBH following referrals by physicians at local clinics controlling for the difference in the case mixes of the HIE and non-HIE groups, which needs to be analyzed with a linear regression model: Yi = ˛ + ˇHIEi +
j PGij + εi
j
in which i = subscript for episodes; j = subscript for patient groups; Y = log-transformed measure of resource utilization; HIE = 1 if the episode is in the HIE group and 0 otherwise; PGj = 1 if the episode is associated with the jth patient group and 0 otherwise; ˇ, j = coefficients; ε = error term. We log-transformed the dependent variables, and the percentage difference of a resource utilization measure between the HIE and the non-HIE groups was derived with the estimate of the ˇ coefficient: 100 × (eˇ¨ − 1). In addition to resource utilization, we also examined the magnitude of information transmitted to SNUBH from referring clinics. We computed descriptive statistics of the magnitude of information transmitted to SNUBH from referring clinics as well as the measures of resource utilization, and we tested the statistical significance of the differences between the HIE and non-HIE groups with the Wilcoxon ranksum test.
2.3.
Study subjects and data
The initial HIE group included all episodes referred to SNUBH from 35 HIE clinics in which treatment was started at the hospital from June 2009 through October 2010. The non-HIE group included those cases referred by 59 non-HIE clinics (Fig. 1). We assigned KDRG and KOPG codes to each episode, and retained those coded groups that contained 2 or more episodes in each of the HIE and non-HIE groups: 100 KOPGs and 29 KDRGs. The final study dataset included a total of 1265 HIE episodes and 2702 non-HIE episodes. The sizes of the 35 HIE clinics measured by the number of practicing physicians ranged from 1 to 5 with a mean of 1.86, and the sizes of the 59 non-HIE clinics ranged from 1 to 14 with a mean of 1.81; the means were not significantly different. The 3 most frequent specialties among both HIE and non-HIE clinics were internal medicine (34%, 18%), otorhinolaryngology (12%, 16%), and ophthalmology (12%, 14%). Table 1 presents general characteristics of study subjects. The average age, the gender of patients and the type of episode among HIE and non-HIE groups did not significantly differ. Approximately 89% of episodes in this study reflected cases
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661
Fig. 1 – Study subjects.
consisting of only outpatient care. The 3 most frequently assigned KOPGs among HIE episodes without hospitalizations reflect minor ophthalmological tests and procedures (6.7%), symptoms and signs involving the circulatory and respiratory systems (4.8%), and endoscopy of the upper airway (4%). Similar symptoms were among the most treated in the non-HIE episodes: minor ophthalmological tests and procedures (7.3%), superficial needle biopsy (7%), and otorhinolaryngologic function tests (6%). The 3 most frequently assigned KDRGs among HIE episodes with hospitalizations were lens procedures with large incisions (10.7%), inguinal and femoral hernia procedures without resection of intestine (7.1%), and major thyroid procedures (6.4%). Among non-HIE episodes, they included major thyroid procedures (9.7%), gastroscopy for non-major digestive disease (8.4%), and major retinal and vitreous procedures without lens procedures (6.5%). We studied 9 measures of resource utilization incurred during an episode of care at SNUBH: total charges; costs for medication as well as clinical laboratory, pathological
diagnostic, function, and diagnostic imaging tests; numbers of orders, outpatient visits, and inpatient days. The entire population of South Korea is covered either by the National Health Insurance Program or by the Medical Aid Program, which are both administered by the National Health Insurance Service (NHIS). A fee schedule for each calendar year is set by the NHIS, and we computed charges based on the fee schedule of the year 2009. Charges included both physician and hospital fees, both insurer and patient payments for covered services, and patient payment for non-covered services. Charge data were extracted from the hospital accounting system and data for the number of orders, outpatient visits, and inpatient days were extracted from EMRs using computer programs created for this study. We estimated 9 models, one for each measure, to examine the effects of the HIE technology on utilization of different types of resources. We counted the number of information items in 4 categories: prescription of medication, order and results of clinical laboratory tests, order and results of diagnostic imaging
Table 1 – General characteristics of study subjects. HIE group
Non-HIE group
Characteristic
(n = 1265)
(n = 2702)
Mean age in years (SD) Gender (%) Male Female Type of episode (%) W/o hospitalization (outpatient visits only) W/hospitalization (outpatient and inpatient care)
43.4 (25.1)
44.2 (24.5)
0.65a
611 (48%) 654 (52%)
1237 (46%) 1465 (54%)
0.14b
1125 (89%) 140 (11%)
2381 (89%) 321 (11%)
0.46b
a b
Wilcoxon test. Pearson’s chi-square test.
P-value
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Table 2 – Descriptive statistics and comparison of group means of the study variables for the health information exchange (HIE) and non-HIE groups. HIE group Variable
Mean
Episodes w/o hospitalization (N for HIE group = 1125, for non-HIE group = 2381) 244,049 Total chargesb 6026 Charges for drugb 5072 Charges for clinical pathology testsb 38,112 Charges for pathological diagnosisb 63,728 Charges for function testsb 95,238 Charges for diagnostic imagingb Num. of orders 6.30 Num. of outpatient visits 1.90 Num. of info. items exchanged: drug 1.65 Num. of info. items exchanged: clinical laboratory tests 2.16 Num. of info. items exchanged: diagnostic imaging 0.01 Num. of info. items exchanged: treatment procedures 0.06 Episodes w/ hospitalization (N for HIE group = 140, for non-HIE group = 321) 2123,910 Total chargesb 138,863 Charges for drugb 92,408 Charges for clinical pathology testsb 64,624 Charges for pathologicaldiagnosisb 148,478 Charges for function testsb 85,611 Charges for diagnostic imagingb Num. of orders 53.35 Num. of outpatient visits 4.10 Length of hospital stay 3.21 Num. of info. items exchanged: drug 1.24 Num. of info. items exchanged: clinical laboratory tests 2.34 Num. of info. items exchanged: diagnostic imaging 0.03 Num. of info. items exchanged: treatment procedures 0.05 a b
P-valuea
SD
Mean
SD
281,053 66,462 18,053 62,899 105,601 207,474 6.66 0.72 5.86 7.17 0.14 0.24
274,622 7683 7418 42,059 70,165 107,540 7.00 1.89 0.18 0.95 0.02 0.02
293,267 75,510 21,537 75,045 110,019 204,890 7.13 0.68 0.75 4.69 0.05 0.15
<0.001 0.16 0.003 0.98 0.06 0.015 <0.001 0.95 <0.001 0.03 0.47 <0.001
2809,208 204,518 208,816 128,667 502,387 256,850 50.27 1.37 3.06 2.73 5.95 0.21 0.22
2656,634 152,301 166,638 139,860 186,474 141,426 61.48 3.38 3.90 0.14 1.74 0.05 0.02
2865,746 164,110 199,943 137,457 434,875 275,319 42.51 1.44 3.19 0.60 7.05 0.24 0.16
0.002 0.73 <0.001 <0.001 <0.001 <0.001 0.04 <0.001 0.09 <0.001 0.13 0.48 0.03
Wilcoxon test. Unit = Korean Won (1 US Dollar = 1168 Korean Won as of December 31, 2009).
tests, and order of treatment procedures. Data on HIE-group information exchanges were extracted from the HIE system using a computer program written for this study, and using the identical logic used to create the data-extracting computer program for the HIE database, we manually extracted data for the non-HIE group from referral letters issued by clinic physicians and medical records and imaging films supplied by patients. About 28% of patients in the non-HIE group brought copies of medical records and/or imaging films to the hospital, and medical records and imaging films are scanned and uploaded to the hospital’s EMR system by a staff member of the office of referrals at the time of registration. A reviewer performed the entire extraction of data for the nonHIE group and another reviewer went over the data extraction and made notes when she found errors or discrepancies. The first reviewer subsequently examined the notes and finalized the data extraction.
3.
Non-HIE group
Results
3.1. Descriptive statistics and comparison of group means Without controlling for the differences in the case mixes of episodes in the HIE and non-HIE groups, we found that the mean total charges and the mean number of orders
were significantly lower in the HIE group compare to the non-HIE group: the mean for episodes involving only outpatient services was 244,049 KRW in the HIE group whereas the mean was 274,622 KRW in the non-HIE group (P < 0.001), and the mean total charges for episodes with hospitalization was 2123,910 KRW in the HIE group whereas the mean was 2656,634 KRW in the non-HIE group (P = 0.002) (Table 2). The mean charges for various types of resources we studied, except for medication and pathological diagnosis for episodes involving only outpatient services and medication for those with hospitalizations, were significantly different between the two groups. For episodes with hospitalizations, the mean number of outpatient visits was significantly lower in the non-HIE group than in the HIE group (4.1 and 3.38 for the HIE and non-HIE groups, respectively; P < 0.001) whereas the mean length of hospital stay was shorter in the HIE group than in the non-HIE group (3.21 and 3.90 for the HIE and non-HIE groups, respectively; P = 0.09). We found physicians at SNUBH possessed more information about the care given at the referring clinics when they treated patients referred from HIE clinics than when they treated patients from non-HIE clinics. The mean numbers of information items transmitted to SNUBH were higher in the HIE group for the types of information studied, particularly for medication and treatment procedures, regardless of whether
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Table 3 – Effect of using health information exchange (HIE) on charges and utilization as estimated with the regression models (N = 3967). Dependent variable
Model r-square (%)
Total charges Total charges for drug Total charges for clinical laboratory tests Total charges for pathological diagnosis Total charges for function tests Total charges for diagnostic imaging Num. of orders Num. of outpatient visits Length of hospital staya a
Coefficient estimate of the HIE dummy variable (ˇ)
49 61 54 31 39 31 20 35 80
P-value of the estimate
−0.14 −0.20 −0.77 −1.41 −1.30 −1.62 −1.01 0.02 −0.06
<0.001 0.33 <0.001 <0.001 <0.001 <0.001 <0.001 0.13 0.16
% Increase or decrease compare to non-HIE group (%) −13 −18 −54 −76 −73 −80 −63 2 −6
The model was analyzed with 461 episodes that had inpatient care.
the patient was hospitalized or only received outpatient care. The mean number of information items as to medication was 1.65 for episodes without hospitalization in the HIE group whereas the mean was 0.18 in the non-HIE group, and the mean for episodes with hospitalization was 1.24 in the HIE group whereas the mean was 0.14 in the non-HIE group.
3.2.
Effect of HIE on resource utilization
The R2 values of the regression models with the HIE and patient-group dummy variables were modestly high for all 9 models: They ranged from 20% (number of orders) to 80% (length of hospital stay) (Table 3). The total charges incurred during an episode of care at SNUBH for patients referred by clinic physicians were approximately 13% lower for the HIE group than for the non-HIE group (estimated after controlling for the difference in case mixes of patients in the two groups): P < 0.001. Similarly, 63% fewer orders were prescribed during an episode categorized in the HIE group (P < 0.001) than in the non-HIE group. Total charges for 4 types of diagnostic tests – clinical laboratory, pathological diagnosis, function, and imaging – were significantly lower in the HIE group, and the percentage difference ranged from 54% (clinical laboratory tests) to 80% (diagnostic imaging). Although the total charges for medications were lower for those in the HIE group, the difference was not statistically significant. Likewise, the length of hospital stay for cases categorized as HIE was less than for those in the non-HIE group, but the difference was not statistically significant (6%, P = 0.16). The greater number of outpatient visits by HIE users showed a small and statistically insignificant difference over that for the non-HIE group (2%, P = 0.13).
4.
Discussion
4.1.
Principal results
that of patients referred by physicians at non-participating clinics. To control for differences in disease types of cases in the 2 groups, we used patient classification codes in linear regression models. Study findings empirically evidenced savings in healthcare costs and showed the potential of an HIE to improve quality of care as well. Total charges and charges for diagnostic tests were lower in the HIE group than in the nonHIE group as hypothesized and predicted in previous studies [2,10,25–27] and the total cost savings per episode under an HIE, as estimated in this study, was 13%. Further, physicians at SNUBH had better access to information about care given to patients from referring clinics. The number of orders prescribed during an episode of care at SNUBH was significantly fewer with the use of the HIE technology, and commensurate cost savings in diagnostic tests appeared firm and significant. The percentage reduction in charges for the 4 types of diagnostic tests studied ranged from 54% to 80%. We confirmed in the examination of the system log that physicians at SNUBH almost always look at patients’ care information exchanged in the HIE system. In a previous study [20], we reported that the most needed and valued information indicated by physicians related to pathology, laboratory, and diagnostic imaging along with medication and working diagnoses. The empirical findings we report in this study confirm the subjective perceptions of physicians that we had previously measured; however, physician agreement about the potential benefits of cost savings was relative low compared to their agreement about the potential benefit of HIEs in terms of quality. We found costs for medications were lower in the HIE than in the non-HIE group, but the difference was not significant. Care given at SNUBH was inherently different from that provided at referring clinics (the very reason patients were referred to SNUBH from local clinics), and this treatment incomparability may explain the lack of differences in the costs of medication.
4.2.
In this study, we quantitatively assessed the potential of HIEs to contain healthcare costs. We compared resource utilization at a tertiary care hospital of patients referred by physicians from local clinics participating in the HIE pilot program to
Limitations
The study findings should be interpreted within the context of the study design and limitations. First, in this study, we only examined episodes of tertiary care based on referrals to a hospital from local clinics. Future studies should explore empirical evidence on the effects of the HIE
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technology in other types of episodes that involve care with multiple providers. Second, savings of healthcare costs in this study could be underestimated because the scope of the study only included care delivered at SNUBH; episodes of care for patients sent back to referring clinics were not included. In a previously published study [20], we found that physicians in clinics were more likely to find useful information in the HIE system than their counterparts do at the tertiary care hospital, and the savings potential could be larger when cases referred back to the clinics are considered. Further, study results did not include savings in administrative and clerical costs of healthcare providers such as copying and scanning medical records, uploading them to the EMR system, and mailing or e-mailing health information to other providers. Third, we only examined charges and did not attempt to measure and monetize benefits in the quality domain, which could result in underestimation of beneficial outcomes of the HIE. According to the results of both physician and patient surveys, participants’ appreciation about the quality benefits associated with the technology were higher than they were concerning the benefits of cost savings [20,21]. Fourth, workflow at SNUBH was established when the EMR system was rolled out in 2004, and no significant changes were made to it with the implementation of the HIE. Previous studies indicated that workflow would significantly influence the impact of the technology, and we cannot make an assumption on how workflow issues have contributed to our findings [10,12,13,28]. Fifth, caution should be exercised with regard to the generalizability of study findings. The payment is based on a fee-for-service mechanism, and policy initiatives to contain healthcare costs are unsubstantial in South Korea. Further, due to poor financial incentives from increases in revenue stemming from the salary structure and the public ownership of their facility, SNUBH physicians feel less pressured than their counterparts at other hospitals and clinics to increase revenue. Lastly, the study may not be free from selection biases, particularly the bias in quality between the HIE and non-HIE clinics. Although sizes of HIE and non-HIE clinics were similar, we did not have access to patient care information at non-HIE clinics and could not determine whether the quality of care at those non-HIE clinics were comparable to the quality provided at HIE clinics. Further, the difference in the case mixes of the HIE and non-HIE groups may not have been addressed adequately in the analytical models because of the collapses of age and complication and comorbidity categories. There were no reported cases of patients’ opting out of the HIE group; therefore, the patients’ selection bias within the HIE group is not of concern.
5.
Conclusions
In this study, we showed HIE technology improved physicians’ access to clinical information at referring clinics, which appeared to reduce diagnostic test utilization and healthcare costs. However, substantial re-alignment of providers’ incentives must be followed to encourage widespread adoption
of the technology and the realization of the commensurate benefits of it, particularly in South Korea due to the fee-for-service payment mechanism. Among critical factors for successful adoption of the HIE technology as suggested in previous literature, the need for fair allocation of benefits and costs among stakeholders was substantiated in this study [4,9,11,12,29]. The major beneficiary of the cost savings shown in this study was the payer, who may need to subsidize providers’ investment in the technology and/or share savings with them. Although we did not report in this study, we found savings in the hospital’s administrative and clerical costs and in physicians’ time at SNUBH and the magnitude of the savings was about 30% of the payer’s savings. We reported in the previous study that SNUBH physicians expressed their concern about the financial burden that comes with the technology [20]. Although physicians appeared less concerned about provider risk, providers may lose revenue with an HIE in a fee-for-service based payment system [20]. The financial benefits to patients are limited because they are responsible only for the coinsurance portion of healthcare costs for covered services and for expenses of non-covered services. The actual amount of savings for 89% of individual episodes, which consisted of outpatient visits only, accumulated to 35,700 Korean Won (KRW, 31 USD) with the mean total charges for the non-HIE group (Table 2) coming to 274,622 KRW (235 USD). The savings for patients came to approximately 16,065 KRW (14 USD) with 45% coinsurance imposed by the NHIS for outpatient visits to tertiary care hospitals. We had reported that patients’ perceptions reflect the lack of impact exerted by such a small savings but we also saw that patients were enthusiastic about the technology, not because of its potential for a reduced burden of healthcare costs, but because of the convenience and quality of care they experienced with the technology [21]. Despite lack of physician or patient enthusiasm for HIE costs savings, the magnitude of savings would be significant for the insurer, NHIS, across multiple provider settings. A study undertaken in Massachusetts estimated that 57% of all acute care visits involved care at multiple hospitals [30]. Multifaceted initiatives to contain healthcare costs and to improve healthcare quality through payment reform and efforts to align stakeholder incentives are needed for wide adoption of an HIE and full realization of the technology benefits.
Authors’ contribution Hayoung Park, PhD conceived and designed the study, analyzed data, interpreted findings, and drafted the article. Sang-il Lee, MD PhD conceived and designed the study, interpreted findings, and drafted the article. Yoon Kim, MD PhD reviewed the study design and interpretation of study findings as well as drafted the article. Eun-Young Heo, MS collected data, assured data quality, and interpreted data as well as drafted the article. Hee Hwang, MD PhD and Jeong-Whun Kim, MD PhD reviewed the study design and interpretation of study findings as well as drafted the article. Kyooseob Ha, MD PhD conceived and designed the study, interpreted study findings,
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Summary points What was already known on the topic: [5]
• The HIE technology is expected to improve the quality and efficiency of care at the same time mainly based on conceptual hypotheses; empirical evidence with quantitative data from an operational HIE is sketchy. • Studies reported savings of healthcare cost and reduced utilization of healthcare at emergency departments. What this study added to our knowledge: • Quantified savings of healthcare costs where patients are referred by physicians at community clinics to a tertiary hospital for further complicated care. • Sources of savings included clinical laboratory tests, pathological diagnosis, function tests, and diagnostic imaging, but were not seen in drugs, outpatient visits and hospital stays.
drafted the article, and directed the pilot program as well. All the authors revised the manuscript critically for important scholarly content, and provided final approval of the version submitted.
[6]
[7]
[8]
[9]
[10]
[11]
[12]
Competing interests None.
[13]
Acknowledgements This study was funded by a grant from the Korea Healthcare Technology R&D Project (A050909) and was partially supported by a grant from the Korea Healthcare Technology R&D Project (A112067) of the Ministry of Health and Welfare of the Republic of Korea.
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