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The Kaiser Permanente Electronic Health Record: Transforming And Streamlining Modalities Of Care



We examined the impact of implementing a comprehensive electronic health record (EHR) system on ambulatory care use in an integrated health care delivery system with more than 225,000 members. Between 2004 and 2007, the annual age/sex-adjusted total office visit rate decreased 26.2 percent, the adjusted primary care office visit rate decreased 25.3 percent, and the adjusted specialty care office visit rate decreased 21.5 percent. Scheduled telephone visits increased more than eightfold, and secure e-mail messaging, which began in late 2005, increased nearly sixfold by 2007. Introducing an EHR creates operational efficiencies by offering nontraditional, patient-centered ways of providing care.
The Kaiser Permanente
Electronic Health Record:
Transforming And Streamlining
Modalities Of Care
EHRs can help achieve more-efficient contacts between patients and
providers, while maintaining quality and satisfaction.
by Catherine Chen, Terhilda Garrido, Don Chock, Grant Okawa, and
Louise Liang
ABSTRACT: We examined the impact of implementing a comprehensive electronic health
record (EHR) system on ambulatory care use in an integrated health care delivery system
with more than 225,000 members. Between 2004 and 2007, the annual age/sex-adjusted
total office visit rate decreased 26.2 percent, the adjusted primary care office visit rate de-
creased 25.3 percent, and the adjusted specialty care office visit rate decreased 21.5 per-
cent. Scheduled telephone visits increased more than eightfold, and secure e-mail
messaging, which began in late 2005, increased nearly sixfold by 2007. Introducing an EHR
creates operational efficiencies by offering nontraditional, patient-centered ways of provid-
ing care. [Health Affairs 28, no. 2 (2009): 323–333; 10.1377/hlthaff.28.2.323]
Agrowing body of literature confirms the value of electronic
health records (EHRs) in improving patient safety, improving coordination
of care, enhancing documentation, and facilitating clinical decision making
and adherence to evidence-based clinical guidelines.1However, less is known
about EHRs’ impact on the efficiency of outpatient care. A recent Congressional
Budget Office (CBO) report notes the paucity of documented benefits of health in-
formation technology (IT) for providers and hospitals that are not part of inte-
grated systems.2In this paper we report on the impact of implementing an inte-
grated EHR system on the use of various types of ambulatory care in one Kaiser
Permanente (KP) region as an example of impact throughout the entire system.
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 323
DOI 10.1377/hlthaff.28.2.323 ©2009 Project HOPE–The People-to-People Health Foundation, Inc.
The authors are all affiliated withKaiser Permanente (KP). Catherine Chen ( is manager,
National Clinical Systems Planning and Consulting, at the KP headquarters in Oakland, California. Terhilda
Garrido is vice president, Strategic Operations, there. Don Chock is director, Performance Assessment, at KP
Hawaii in Honolulu. Grant Okawa is associate medical director, Knowledge Management, of the Hawaii
Permanente Medical Group. Louise Liang is senior vice president, Quality and Systems Support, in Oakland.
KP is the largest U.S. not-for-profit integrated health care delivery system, serv-
ing 8.7 million members in eight regions. Members receive the entire scope of
health care: preventive care; well-baby and prenatal care; immunizations; emer-
gency care; hospital and medical services; and ancillary services, including phar-
macy, laboratory, and radiology. Nationwide, KP employs approximately 156,000
technical, administrative, and clerical personnel and caregivers and 13,000 physi-
KP HealthConnect
In 2004, KP began implementing KP HealthConnect, a comprehensive health
information system with numerous functionalities, including (1) an EHR with
comprehensive documentation across care settings—inpatient and outpatient,
clinical decision support, and complete, real-time connectivity to lab, pharmacy,
radiology, and other ancillary systems; (2) secure patient-provider messaging
available through a member Web site that also provides personal health records;
and (3) electronic interprovider messaging about care that is automatically incor-
porated into patients’ records.
The purpose of our study was to examine the impact of KP HealthConnect on
several types of ambulatory care patient contacts: outpatient, urgent care, and
emergency department (ED) visits; external referrals; scheduled telephone visits;
and secure patient-physician e-mail messaging.
Study Data And Methods
The KP Hawaii region was the first in Kaiser Permanente to fully implement KP
HealthConnect in the outpatient setting. KP Hawaii has approximately 225,000
members, a figure that was consistent during the four-year study period.
We conducted a retrospective observational study using administrative data.
The baseline year was 2004; KP HealthConnect implementation in primary care
was completed in June 2005, and the patient-provider secure messaging function
became available in September 2005. The comparison year was 2007.
Data on rates of outpatient, urgent care, and ED visits; external referrals; sched-
uled telephone visits; and secure patient-physician messaging were extracted
from the regional data warehouse.3Annual total office visit rates per region were
stratified by primary care and specialty care and age/sex-adjusted to a fixed age/
sex distribution over the time period, using four age categories (0–19, 20–44, 45–
64, and 65+).
Our study included the entire regional membership, allowing us to use the
Wilcoxon-Mann-Whitney test to assess the statistical significance of the changes
between 2004 and 2007 in rates of total office visits, primary care visits, specialty
care visits, scheduled telephone visits, secure patient-physician messaging, exter-
nal referrals, urgent care visits, and ED visits.
324 March/April 2009
Electronic Health Records
Study Findings
nOffice and telephone visits. Age/sex-adjusted total office visits per member
decreased 26.2 percent between 2004 and 2007 (p<0.001), and total scheduled tele-
phone visits per member increased nearly ninefold (Exhibit 1). Exhibit 2 summa-
rizes the changes in office and telephone visits.
nSecure messaging. In September 2005, KP Hawaii launched My Health
HealthConnect. In the remaining months of 2005, members initiated more than
3,000 secure e-mail messages, a rate of 0.03 secure messages per member. In 2006,
members sent nearly 25,000 messages (0.11 per member). In 2007, they sent more
than 51,000 messages (0.23 per member). The increase between 2005 and 2007 was
statistically significant (p<0.001).
The total number of patient contacts via office and telephone visits and secure
messaging increased 8.3 percent after EHR implementation, from 5.18 contacts per
member per year in 2004 to 5.61 contacts per member per year in 2007 (p<0.001).
nOther factors. We explored other factors that could explain decreased use of
ambulatory care visits. Enrollment in KP Hawaii did not change over the four-year
study period, nor did the proportions of members over age sixty-five (12 percent)
and those with at least one chronic condition (29 percent). The ratio of providers to
members remained stable over time at 1.9 physicians per 1,000 members. The rate of
referrals to external providers decreased 53 percent between 2004 and 2007
The rate of ED and urgent care visits increased between 2004 and 2007—ur-
gent care visits by 19 percent (p<0.001) and ED visits by 11 percent (p<0.001)
(Exhibit 3).
nQuality and patient satisfaction. KP Hawaii captures Healthcare Effective-
ness Data and Information Set (HEDIS) data as part of its routine quality surveil-
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 325
Changes In Office Visit Rates Among Kaiser Permanente (KP) Hawaii Members,
SOURCE: Authors’ analysis using data from the Kaiser Permanente Hawaii Data Warehouse and secure messaging database.
Office visits per member
1999 2000 2001 2002 2003 2004 2005 2006 2007
Primary care
Electronic health record implemented
lance.4Between 2004 and 2007, many scores were not comparable over time because
of changes in the HEDIS measure set. For the majority of measures that were compa-
rable, performance remained stable during the study period (Exhibit 4). Overall
quality was, at the least, maintained.
We were unable to use Consumer Assessment of Healthcare Providers and Sys-
tems (CAHPS) data to assess patient satisfaction because measures were not com-
parable across all years.5However, results from KP Hawaii member satisfaction
surveys remained essentially unchanged. In 2004, 84 percent of surveyed KP Ha-
waii members rated their overall visit satisfaction at 8 or above on a scale of 1 to 10;
in 2007, 87 percent did so. In 2004, 78 percent of KP Hawaii members rated the
326 March/April 2009
Electronic Health Records
Changes In Office Visit Versus Telephone Visit Rates Among Kaiser Permanente (KP)
Hawaii Members, 1999–2007
SOURCE: Authors’ analysis using data from the Kaiser Permanente Hawaii Data Warehouse and secure messaging database.
Visits per member
1999 2000 2001 2002 2003 2004 2005 2006 2007
Office visits
Scheduled phone visits
Electronic health record implemented
Ambulatory Care Contact Per Member Rates Among Kaiser Permanente (KP) Hawaii
Members, Selected Years 2004–2007
Type of contact 2004 2005 2007 Net change Percent changea
Total office visitsb
Primary care
Specialty care
Scheduled telephone visits
Secure e-mail messaging
All ambulatory care contacts 5.18 c5.61 0.43 8
External referrals
Urgent care
ED visits
SOURCE: Authors’ analysis using data from the Kaiser Permanente Hawaii Data Warehouse and secure messaging database.
NOTE: ED is emergency department.
aAll results are statistically significant (p< 0.001).
bThe number of total office visits is greater than the sum of primary and specialty care visits because total office visits include
care rendered by nurse practitioners, physician assistants, registered nurses, optometrists, social workers, and rehabilitative
therapists, as well as physicians.
cNot applicable.
dNot available.
level of interest and attention of their health care providers at 8 or above; in 2007,
79 percent did so. Additionally, in 2007, 90 percent rated their satisfaction with
telephone visits at 8 or above.6
Discussion And Policy Implications
We examined the impact of an integrated EHR on ambulatory care use and
found a 26.2 percent decrease in the annual age/sex-adjusted total office visit rate
over four years. In 1999, office visits accounted for 99.6 percent of all ambulatory
care contacts. Eight years later, they represented 66 percent of patient contacts.
Scheduled telephone visits accounted for 30 percent of patient contacts, and se-
cure messaging represented the remaining 4 percent (Exhibit 5). Between 2004
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 327
Healthcare Effectiveness Data And Information Set (HEDIS) Scores Of Kaiser
Permanente (KP) Hawaii Members, 2004 And 2007
Measure 2004 2007 Trenda
Commercial population
Childhood immunization status—combination 2
Appropriate testing for children with upper respiratory infection
No change
Appropriate testing for children with pharyngitis
Colorectal cancer screening
Breast cancer screening in women ages 52–69
Chlamydia screening for women
Ages 16–20
Ages 21–25
All, ages 16–25
Comprehensive diabetes care
HbA1c testing
Poor HbA1c control
Use of imaging studies for low back pain
Antidepressant medication management
Effective acute-phase treatment
Effective continuation-phase treatment
Follow-up after hospitalization for mental illness
Within 7 days
Within 30 days
Medicare population
Colorectal cancer screening
Breast cancer screening in women ages 52–69
Comprehensive diabetes care
HbA1c testing
Poor HbA1c control
Antidepressant medication management
Effective acute-phase treatment
Effective continuation-phase treatment
Osteoporosis management in women with a fracture
SOURCE: Kaiser Permanente Hawaii HEDIS data.
aTrends reflect changes in the HEDIS scores; no statistical significance testing was conducted.
and 2007, these new modalities of care enabled an overall increase in patient con-
tacts and access of 8 percent.
Although ED and urgent care use rose between 2004 and 2007, the increase rep-
resents only approximately 5 percent of the volume of the decrease in total office
visit rates. Therefore, it is unlikely that the rise reflects a shift in the location of
care from office-based sites to ED and urgent care settings. Further, the rise in ED
and urgent care visit rates was delayed relative to the decrease in office visit use,
which suggests alternative causes.
nMaintenance of quality. The majority of twenty-two HEDIS scores that were
comparable between 2004 and 2007 were at least maintained, with a few excep-
tions: poor HbA1c control in both the commercial and Medicare populations, man-
agement of antidepressant medications in the commercial population, and osteopo-
rosis management in women with a fracture in the Medicare population.7
nOrganizational assists. Organizational efforts to shift ambulatory care use
could also explain the changes in rates. Copayments increased $2 per visit per year
between 2004 and 2007 as part of a stepped program to increase consumer cost
sharing in the most prevalent benefit plan. However, previous larger copayment in-
creases were not related to similar decreases in office visit rates.
The initiation of total panel management (TPM) in 2004 might have had a mini-
mal impact on office visit use. In the TPM model of care, primary care teams iden-
tify members of their patient panel who need medications, testing, or other evi-
dence-based care and then use multiple strategies to address these needs, such as
telephone visits and secure messaging, in addition to office visits. TPM can reduce
only 10 percent of KP Hawaii clinics were engaged in TPM during the study pe-
328 March/April 2009
Electronic Health Records
Distribution Of Patient Contacts Over Time Among Kaiser Permanente (KP) Hawaii
Members, 1999–2007
SOURCE: Authors’ analysis using data from the Kaiser Permanente Hawaii Data Warehouse and secure messaging database.
Contacts per member
1999 2000 2001 2002 2003 2004 2005 2006 2007
Scheduled phone visitsOffice visits
Secure messaging
riod. In addition, office visit use uniformly decreased in clinics without TPM.
nAn EMR head start. The existence of an earlier electronic medical record
(EMR) may also have affected our findings. KP Hawaii had partially phased in an-
other electronic system, Clinical Information System (CIS). At the time of KP
HealthConnect implementation, a third of care sites had had full CIS functionality
for just over two years; the rest had read-only access.8An 87 percent drop in daily
pulls of paper charts after KP HealthConnect was implemented indicates that CIS
was largely used alongside paper charts. However, the two systems shared some
functionality. It is possible that CIS also slightly reduced office visits, which would
have attenuated the effects we observed from KP HealthConnect.
nEfficiency and productivity. We did not examine changes in the efficiency or
productivity of providers immediately around the time of implementation. Tempo-
rary decreases in productivity of as much as 15 percent are common at implementa-
EHRs may increase the time it takes to document patient visits.10 We did not
examine the impact of KP HealthConnect on net efficiency. Doing so would have
required quantifying costs of increased documentation time and savings in nurs-
ing, receptionist, and appointment clerk time from decreased office visit rates. In
addition, costs to patients of office visits—such as out-of-pocket expenses and
time costs of travel, parking, and missed school or work—are often overlooked
when one is calculating net efficiency. An average visit in the community can con-
sume 103 minutes (Exhibit 6). In contrast, e-mail messaging and scheduled tele-
phone visits consume much less time; logic suggests that the efficiency gains offset
any increases in documentation time.
nStudy limitations. Limitations of our study include the fact that the system ar-
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 329
Average Time Spent By Patients For An Ambulatory Care Visit In The Community,
Patient activity Minutes
Travel to and from ambulatory carea
Receptionist check-in/outb
Waiting room waitc
Exam room waitd
Time with providere
SOURCES: See below.
aC.B. Forrest and B. Starfield, “Entry into Primary Care and Continuity: The Effects of Access,”American Journal of Public
Health 88, no. 9 (1998): 1330–1336.
bL.A. Backer, “Strategies for Better Patient Flow and Cycle Time,” Family Practice Management 9, no. 6 (2002): 45–50.
cK.M. Leddy, D.O. Kaldenberg, and B.W. Becker, “Timeliness in Ambulatory Care Treatment: An Examination of Patient
Satisfaction and Wait Times in Medical Practices and Outpatient Test and Treatment Facilities,” Journal of Ambulatory Care
Management 15, no. 42 (2003): 138–149.
dLeddy et al., “Timeliness in Ambulatory Care Treatment.”
eKaiser Permanente, internal study, 2008.
chitecture and implementation schedule precluded a randomized controlled trial.
We were also unable to compare our findings against utilization rates in other KP
regions because they were all in various stages of implementing KP HealthConnect
during our study period. However, we note that the rate of ambulatory care visits
has been rising since the mid-1990s in the United States as a whole.11
Additional limitations include the fact that our data on quality and patient sat-
isfaction were drawn from contemporaneous tools and were not specific to this
study. Changes in the HEDIS measure set between 2004 and 2007 restricted our
ability to compare quality before and after EHR implementation. The long-term
effects of telephone visits and secure patient-physician messaging on efficiency,
quality, and patient satisfaction are unknown and require measuring impacts dur-
ing a longer time period.
Our report falls short of a comprehensive evaluation of the impact of KP
HealthConnect, which would require monetizing efficiency shifts. This is chal-
contrast to fee-for-service systems, Permanente Medical Group physicians receive
a fixed salary regardless of the number of services rendered. Permanente Medical
Groups provide medical care for members under a mutually exclusive contract
with the Kaiser Foundation Health Plan.
nEconomic impact of EHRs. Further study may yield important findings
about the overall economic impact of implementing a comprehensive EHR in the
outpatient setting. It should be noted, however, that the CBO suggests that the
adoption of more health IT is generally not sufficient to produce significant cost sav-
ings in the absence of incentive structures that reward (or, at a minimum, do not
disincent) efficiencies.12 The U.S. Department of Health and Human Services (HHS)
suggests that a comprehensive evaluation would include measures of quality, pa-
tient safety, costs of direct care, administrative efficiencies, decreased paperwork,
and expanded access.13
nConsistency with previous KP study. Our findings are consistent with those
14 Decreased office visits and increased scheduled
telephone visits indicate that to some degree, telephone visits can substitute for of-
fice visits with immediate access to complete, current patient information via an in-
tegrated EHR. However, the previous study did not involve the more comprehensive
KP HealthConnect system or secure e-mail messaging. KP also documented that se-
cure e-mail messaging can provide an asynchronous, convenient substitute for some
office and telephone visits.15
The 26.2 percent reduction in office visits indicates greater efficiency of care
with an integrated EHR. With complete patient data available, unnecessary and
marginally productive office visits are reduced or replaced with telephone visits
and secure e-mail messaging supported by easy access to patients’ medical rec-
ords. For example, doctors reported that the EHR enabled them to resolve pa-
tients’ health issues in the first contact or with fewer contacts.16 In sum, our study
330 March/April 2009
Electronic Health Records
strongly suggests that an integrated and comprehensive EHR shifts the pattern of
ambulatory care toward more-efficient contacts for patients and providers while
at least maintaining quality of care and patient satisfaction.
nImportance of aligned financial incentives. Importantly, our results were
obtained in an integrated delivery system with an economic model that aligns finan-
cial incentives with providing effective and efficient care, regardless of how that care
is delivered. As the CBO notes, “How well health IT lives up to its potential depends
in part on how effectively financial incentives can be realigned to encourage the op-
timal use of the technology’s capabilities.”17
A specific example from KP Hawaii illustrates the potential that health IT
holds for transforming care when incentives are properly aligned. The Hawaii re-
gional team of nephrologists took advantage of the ready availability of compre-
hensive clinical information on all patients to risk-stratify the entire regional pop-
ulation with chronic kidney disease. Using evidence-based guidelines to
electronically review the health records of thousands of members, they instituted
proactive, risk-driven, electronic consultations instead of relying only on primary
care providers to refer patients for specialty care. These consultations sometimes
recommended traditional specialty visits but often provided care recommenda-
tions remotely, using electronic communication. Nephrologists used KP Health-
Connect’s internal messaging feature to provide KP primary care physicians with
clinical management advice tailored to specific patients. Over three years, major
improvements occurred in key indicators of quality of care for chronic kidney dis-
nPolicy implications. Until public and private policies reward care strategies
other than face-to-face visits, few providers will adopt them. Only in 2008 did the
Centers for Medicare and Medicaid Services (CMS) add codes for telephone con-
tacts that are intended to supplant office visits and for online management. Medi-
care, however, listed both services as noncovered for 2008, leaving it to the discre-
tion of individual insurers whether to pay for these services.19 Private insurers
reimburse providers for online visits on a very limited basis.20
nFactoring in consumers’ preferences. Aligning nonfinancial incentives for
using EHRs to improve the efficiency of care is also necessary. For instance, the Na-
tional Committee for Quality Assurance (NCQA) relies on office visits as the pre-
dominant indicator of quality-related activity.21 However, consumer choice is a key
component of value-driven care.22 Increasing evidence identifies patients’ clear pref-
erences for and satisfaction with e-mail messaging with their doctors.23
The KP experience is similar; among users of KP HealthConnect in KP North-
west, 85 percent rated their satisfaction as 8 or 9 on a nine-point scale.24 In a sepa-
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 331
“Until public and private policies reward care strategies other than
face-to-face visits, few providers will adopt them.”
rate survey, 85 percent of users indicated that the ability to communicate electron-
ically with their physicians enabled them to better manage their health.25
If face-to-face visits remain the gold standard for quality, care standards will
not reflect the preference of consumers for alternative, more convenient modes of
care when they are appropriate or reinforce more efficient care delivery options.
Kaiser permanente’s work in this area is still in progress. We will
continue to evaluate the impacts of KP HealthConnect on care and admin-
istrative efficiencies, quality, safety, and access over the long term. This re-
port is interim, insofar as KP continues to innovate and improve workflows to cre-
ate a new value equation for patients and purchasers. However, it provides a view
into the transformation of ambulatory care that emerges and is increasingly possi-
ble when technology and incentives align with patients’ preferences.
The authors thank the many physicians, operations leaders, and analysts in the Kaiser Permanente Hawaii region
for their contributions. In particular, they thank Yvonne Zhou, Amy Watts, Cynthia Okamura, Fred Shaw, Rod
Pederson, Brian Lee, Ravi Poorsina, and Samantha Quattrone for their support and insights; Arnold Matsunobu,
writing this paper.
1. See, for example, R. Kaushal, K.G. Shojania, and D.W. Bates, “Effects of Computerized Physician Order En-
try and Clinical Decision Support Systems on Medication Safety: A Systematic Review,” Archives of Internal
Medicine 163, no. 12 (2003): 1409–1416; L.C. Burton et al, “Using Electronic Health Records to Help Coordi-
nate Care,” Milbank Quarterly 82, no. 3 (2004): 457–481; J. Hippisley-Cox et al., “The Electronic Patient Rec-
ord in Primary Care—Regression or Progression? A Cross Sectional Study,” BMJ 326, no. 7404 (2003):
1439–1443; J. Butler et al., “Improved Compliance with Quality Measures at Hospital Discharge with a
Computerized Physician Order Entry System,” American Heart Journal 151, no. 3 (2006): 643–653; and B.
Chaudhry et al., “Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and
Costs of Medical Care,” Annals of Internal Medicine 144, no. 10 (2006): 742–752.
2. Peter R. Orszag, Congressional Budget Office, “Evidence on the Costs and Benefits of Health Information
Technology,” Testimony before the House on Ways and Means Subcommittee on Health, 24 July 2008, (accessed 22 December 2008).
3. Total office visits” include care from medical and osteopathic doctors, resident physicians, nurse practi-
tioners, physician assistants, registered nurses, optometrists, social workers, and rehabilitative therapists.
“Primary care visits” include clinic-based care from internal medicine, family practice, and pediatric physi-
cians. “Specialty care visits” include clinic-based care by other specialty and subspecialty physicians.
“Scheduled telephone visits” include prearranged phone calls between providers and patients. “External
referrals” include only non–Kaiser Permanente ambulatory consultations. “Emergency department visits”
include visits to KP and non-KP emergency departments (EDs). “Urgent care visits” include care at KP ur-
gent care centers; these are not included in total office visits.
4. National Committee for Quality Assurance, “HEDIS and Quality Measurement,” 2008, http://www.ncqa
.org/tabid/59/Default.aspx (accessed 21 November 2008).
5. Agency for Healthcare Research and Quality, “CAHPS: Surveys and Tools to Advance Patient-Centered
Care,” 2008, (accessed 21 November 2008).
6. Kaiser Permanente, internal study, 2007.
7. Hawaii regional clinicians conducted a close review of antidepressant follow-up and noted discrepancies
between care that occurred and care that was “counted” under HEDIS criteria. For instance, if follow-up
on the use of antidepressant medications occurred during a visit but depression was not the primary diag-
nosis, it did not count toward the HEDIS measure. Scheduled telephone visits that were inaccurately
332 March/April 2009
Electronic Health Records
coded as “telephone encounters” also did not count toward the measure.
8. J.T. Scott et al., “Kaiser Permanente’s Experience of Implementing an Electronic Medical Record: A Quali-
tative Study,” BMJ 331, no. 7528 (2005): 1313–1316.
9. D. Gans et al., “Medical Groups’ Adoption of Electronic Health Records and Information Systems,” Health
Affairs 24, no. 5 (2005): 1323–1333.
10. L. Poissant et al., “The Impact of Electronic Health Records on Time Efficiency of Physicians and Nurses: A
Systematic Review,” Journal of the American Medical Informatics Association 12, no. 5 (2005): 505–516.
11. E. Hing, D.K. Cherry, and D.A. Woodwell, “National Ambulatory Medical Care Survey: 2004 Summary,”
Advance Data from Vital and Health Statistics no. 374, 23 June 2006,
ad/ad374.pdf (accessed 22 December 2008); and D.K. Cherry, D.A. Woodwell, and E.A. Rechtsteiner, “Na-
tional Ambulatory Medical Care Survey: 2005 Summary,” Advance Data from Vital and Health Statistics
no. 387, 29 June 2007, (accessed 22 December 2008).
12. Orszag, “Costs and Benefits of Health Information Technology.”
13. U.S. Department of Health and Human Services, “Health Information Technology Home,” 2008, http:// (accessed 21 November 2008).
14. T. Garrido et al., “Effect of Elect ronic Health Records in Ambulatory Care: Retrospective, Serial, Cross Sec-
tional Study,” BMJ 330, no. 7491 (2005): 581.
15. Y.Y. Zhou et al., “Patient Access to an Electronic Health Record with Secure Messaging: Impact on Primary
Care Utilization,” American Journal of Managed Care 13, no. 7 (2007): 418–424.
16. Garrido et al., “Effect of Electronic Health Records.”
17. Orszag, “Costs and Benefits of Health Information Technology,” 7.
18. B. Lee and K. Forbes, “The Role of Specialists in Managing the Health of Populations with Chronic Dis-
ease: The Example of Chronic Kidney Disease” (Unpublished manuscript, Kaiser Permanente, 2008).
19. B. Whitman, “2008 CPT Codes Clarify Billing for Phone and Electronic E/M,” 2008, http://www (accessed 21 November 2008).
20. M. Merrill, “Insurers Reimburse IADMD Members for Online Visits,” He althca re IT News , 29 February 2008, (accessed 21 November 2008).
21. National Committee for Quality Assurance, TheSta te of Health Care Quality 2 007 (Washington: NCQA, 2007).
22. DHHS, “Value-Driven Health Care Home,” (accessed 21 No-
vember 2008).
23. A. Hassol et al., “Patient Experiences and Attitudes about Access to a Patient Electronic Health Care Rec-
ord and Linked Web Messaging,” Journal of the American Medical Informatics Association 11, no. 6 (2004): 505–
513; and K.D. Kleiner et al., “Parent and Physician Attitudes regarding Electronic Communication in Pedi-
atric Practices,” Pediatrics 109,no.5(2002):740744.
24. C.A. Serrato, S. Retecki, and D. Schmidt, “MyChart—A New Mode of Care Delivery: 2005 Personal Health
Link Research Report,” Perman ente Journal 11, no. 2 (2007): 14–20.
25. Kaiser Permanente, internal study, 2006.
Kaiser EHR
HEALTH AFFAIRS ~ Volume 28, Number 2 333
... Le seguenti metodologie di ML sviluppate per specifici task clinici nello scenario della PM sono adatte a costituire il nucleo principale di nuovi sistemi clinici di supporto alle decisioni, utilizzabili dai medici per scopi di prevenzione, screening, diagnosi e follow-up: i) un approccio sparse-balanced Support Vector Machine con lo scopo di predire il diabete di tipo 2 (T2D), utilizzando le informazioni estratte da un nuovo EHR dataset di un medico di medicina generale; ii) un approccio Regression Forest ensemble ad alta interpretabilità con lo scopo di identificare fattori clinici non di routine nei dati EHR per determinare dove sia racchiusa la condizione di insulinoresistenza; iii) un approccio di Multiple Instance Learning boosting applicato ai dati EHR volto a predire precocemente un peggioramento dell'insulino-resistenza (basso vs alto rischio di T2D) in termini di TyG index; iv) un nuovo approccio multitasking semi-supervisionato con lo scopo di predire l'evoluzione a breve termine della patologie renale (cioè il profilo di rischio del paziente) sui dati EHR di un cluster di medici di medicina generale; v) un approccio XGBoosting con lo scopo di predire il SOFA score al quinto giorno, utilizzando solo i dati EHR del giorno di ammissione in unità di terapia intensiva (ICU). Il SOFA score descrive le complicazioni del paziente COVID- 19 in ICU e aiuta i medici a creare profili di rischio dei pazienti COVID-19. La tesi ha anche contribuito alla pubblicazione di nuovi EHR datasets open access (FIMMG dataset, FIMMG obs dataset, FIMMG pred dataset, mFIMMG dataset). ...
... The reason for a strong investment in HIT is the wider adoption of EHR systems. EHRs are expected to improve the national healthcare quality and efficiency [16,17], for example, decreasing unnecessary services, such as repeated laboratory tests every time the patient changes hospital and office visits [18,19]. Moreover, the 1.3. ...
... The reason for a strong investment in Health Information Technology (HIT) is that wider adoption of EHRs will reduce healthcare costs, medical errors [18,20], patient complications and mortality [21,22]. Moreover, the HIT will decrease the use of healthcare services such as laboratory tests and outpatient visits, [18,19], while it will improve the national healthcare quality and efficiency [16,17]. ...
Traditional approaches in medicine to manage diseases can be briefly reduced to the “one-size-fits all” concept (i.e., the effect of treatment reflects the whole sample). On the contrary, precision medicine may represent the extension and the evolution of traditional medicine because is mainly preventive and proactive rather than reactive.This evolution may lead to a predictive, personalized, preventive, participatory, and psycho-cognitive healthcare. Among all these characteristics, the predictive medicine (PM), used to forecast disease onset, diagnosis, and prognosis, is the one this thesis emphasizes. Thus, it is possible to introduce a new emerging healthcare area, named predictive precision medicine (PPM), which may benefit from a huge amount of medical information stored in Electronic Health Records (EHRs) and Machine Learning (ML) techniques.The thesis ecosystem, which consists of the previous 3 inter-connected key points (i.e., PPM, EHR, ML), contributes to the biomedical and health informatics by proposing meaningful ML methodologies to face and overcome the state-of-the-art challenges, that emerge from real-world EHR datasets, such as high-dimensional & heterogeneous data; unbalanced setting; sparse labeling; temporal ambiguity; interpretability/explainability; and generalization capability.The following ML methodologies designed from specific clinical objectives in PM scenario are suitable to constitute the main core of any novel clinical Decision Support Systems usable by physicians for prevention, screening, diagnosis, and treatment purposes:i) a sparse-balanced Support Vector Machine (SB-SVM) approach aimed to discover type 2 diabetes (T2D) using features extracted from a novel EHR dataset of a general practitioner (GP);ii) a high-interpretable ensemble Regression Forest (TyG-er) approach aimed to identify non-trivial clinical factors in EHR data to determine where the insulin-resistance condition is encoded;iii) a Multiple Instance Learning boosting (MIL-Boost) approach applied to EHR data aimed to early predict an insulin resistance worsening (low vs high T2D risk) in terms of TyG index;iv) a novel Semi-Supervised Multi-task Learning (SS-MTL) approach aimed to predict short-term kidney disease evolution (i.e., patient’s risk profile) on multiple GPs’ EHR data;v) A XGBoosting (XGBoost) approach aimed to predict the sequential organ failure assessment score (SOFA) score at day 5, by utilising only EHR data at the admission day in the Intensive Care Unit (ICU). The SOFA score describes the COVID-19 patient’s complications in ICU and helps clinicians to create COVID-19 patients' risk profiles.The thesis also contributed to the publication of novel publicly available EHR datasets (i.e., FIMMG dataset, FIMMG_obs dataset, FIMMG_pred dataset, mFIMMG dataset).
... To ensure the accuracy of the qualitative ndings, four criteria (validity or acceptability, reliability or similarity, transferability and veri cation) proposed by GABA and Lincoln were considered. The researcher attempted to ensure that the ndings re ect the real experiences of participants (15). ...
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Background: Health information system is an integral part of the health system that has a vital role in increasing the efficiency of the health system, especially in primary health care settings. This study was conducted to determine the minimum dataset required in the electronic health record within the health system of Iran as a lower middle income country. Method: This study combines qualitative and quantitative methods. It includes three main stages: reviewing the theoretical foundations of research, designing the main framework for interview questions, conducting a qualitative study by interviewing 42 managers of the health system across the country to determine the minimum dataset in the electronic health. Interviews were carried out from 2020 to 2021. The validity of data was assessed by Delphi method using SPSS 15 software. Results: After reviewing the minimum dataset in the electronic health records of seven countries, 7 main concepts and 23 sub-concepts were extracted from the interviews with experts across the country. Accordingly, 159 information elements were surveyed and a two-round Delphi provided 145 information elements in seven categories of children's program, mothers' program, mental health, elderly, paraclinical services, drug program, and vaccination. Conclusion: Health systems in different countries determine the minimum dataset required in health care setting based on their demographic and epidemiological needs, which can facilitate access to accurate and unambiguous information.
... Participating cardiologists stressed the need for uniform data approaches, accessible to digitally illiterate patients and facilitating rapid diffusion of relevant information to physicians. These have shown substantial promise in several integrated care projects [37][38][39]. ...
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Background Cardiologists play a key role in multidisciplinary care by guiding heart failure (HF) management in the hospital and in the community. Regional implementation of multidisciplinary health care interventions depends on how they perceive collaboration with other health care disciplines, yet research on this topic is limited. This study aimed to explore the views and opinions of cardiologists on multidisciplinary collaboration in HF care. Methods We conducted a qualitative study based on face-to-face semi-structured interviews with 11 Belgian cardiologists between September 2019 and February 2020. We used the Qualitative Analysis Guide of Leuven (QUAGOL) method as guidance for data analysis until data saturation was reached. Results Cardiologists consider the general practitioner (GP) and HF nurse as the most important partners in HF management. Cardiologists identified four problems in current multidisciplinary collaboration: the communication of a HF diagnosis to the patient, advanced care planning, titration of HF medication by the GP and electronic data exchange and communication. Three themes emerged as ideas for improvement of HF care: 1) expansion of the role of the HF nurse, 2) implementation of a structured, patient-centered, and flexible model of disease management program and 3) integrated data approaches. Conclusion Cardiologists value close cooperation with GPs in HF management. They advocate an expanded future role for the HF nurse, increased eHealth, and structured disease management to optimize current HF care.
Building on technological advances and existing currents of a healthcare system in flux, the COVID‐19 pandemic has brought about perhaps the most rapid transformation in human health and healthcare seen in our times. Even as new opportunities such as telemedicine, remote care, and rapid precision health practices are poised to improve access and care for populations, the increasing sophistication of this transformation has brought with it new levels of complexity, fragmentation, and silos. The singular outcome of this system is the vast number of novel ways for miscommunication, loss of information in transition, and breakdowns in the cognitive continuity of care. We refer to these failure modes as “dropping the patient” and adopt a mantra of “don't drop the patient” which examines our emerging health system in the context of patient‐centered continuity. In this light, we investigate bright spots and pitfalls, and we offer insights from Human Factors Engineering, Human Centered Design, and Human System Integration, which provide tools and methods to codesign and codevelop continuous and resilient services that are inclusive, sustainable, and effective. Technological advances, along with global pressures on health care from events such as the COVID‐19 pandemic, have created an information environment in healthcare that is in flux. On the positive side, a widespread adoption of electronic health information systems can transcend barriers to access by moving care to patients through telemedical consults, remote patient monitoring, online self‐management, appointment management, treatment tracking, and population health monitoring. On the negative side, overlaying complex information technologies on healthcare networks that may already be fragmented may increase risks for communication errors. Strengthening communication systems in health care will require an application of human‐centered design principles not just at the level of individual technologies but at the systems level in which technologies, medical protocols, professional training, and patient experiences interact. A key focus of design efforts at the human‐system level is to create a fault‐tolerant sociotechnical environment that minimizes discontinuity in care; that is, to create a new biomedical ethos of “not dropping the patient” as the standard in global health care. Technological advances, along with global pressures on health care from events such as the COVID‐19 pandemic, have created an information environment in healthcare that is in flux. On the positive side, a widespread adoption of electronic health information systems can transcend barriers to access by moving care to patients through telemedical consults, remote patient monitoring, online self‐management, appointment management, treatment tracking, and population health monitoring. On the negative side, overlaying complex information technologies on healthcare networks that may already be fragmented may increase risks for communication errors. Strengthening communication systems in health care will require an application of human‐centered design principles not just at the level of individual technologies but at the systems level in which technologies, medical protocols, professional training, and patient experiences interact. A key focus of design efforts at the human‐system level is to create a fault‐tolerant sociotechnical environment that minimizes discontinuity in care; that is, to create a new biomedical ethos of “not dropping the patient” as the standard in global health care.
Häufig werden Versicherungen als Ursprung von MCOs betrachtet. Auch wenn dies für die Wiederbelebung von Managed Care seit Mitte der 70er Jahre durchaus zutrifft, liegen die Ursprünge in den USA eher bei der Risikoübernahme durch die Leistungsersteller in den 20er Jahren in Form der sogenannten Prepaid Group-PraticesPrepaid Group Practices (PGP) (PGP).
Population health management is an increasingly popular concept in health systems. Driven by growth in ‘big data’, the approach uses aggregated data to identify and manage the health of those deemed ‘at risk’. We use the UK’s response to the COVID-19 pandemic as a lens to critically examine this approach to improving population health, using the policy of ‘shielding’ those at high risk of harm as an exemplar. Firstly, we explore the policy as an example of categorisation, showing that criteria used to identify high-risk population ‘segments’ are never wholly objective, arising out of negotiations taking account of economic, political, or social issues, with the categorization of individuals as in/out of the high-risk group always approximate. Secondly, we consider the construction of risk and demonstrate that focusing on biomedical data brackets out societal factors driving individual risks including deprivation, racial discrimination, and employment status. Finally, we highlight how this framing of COVID-19-associated risk as a biomedical issue leads to a neoliberal focus upon individual rather than societal risk-mitigation approaches. We argue that population health management should be married with traditional public health advocacy and campaigning, digging beneath identified disparities to expose and interrogate the structural factors at work.
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Introduction The availability and routine use of electronic health records (EHRs) have become commonplace in healthcare systems of many high-income countries. While there is an ever-growing body of literature pertaining to their use, evidence surrounding the importance of EHR interoperability and its impact on patient safety remains less clear. There is, therefore, a need and opportunity to evaluate the evidence available regarding this relationship so as to better inform health informatics development and policies in the years to come. This systematic review aims to evaluate the impact of EHR interoperability on patient safety in health systems of high-income countries. Methods and analysis A systematic literature review will be conducted via a computerised search through four databases: PubMed, Embase, Health Management Information Consortium and PsycInfo for relevant articles published between 2010 and 2020. Outcomes of interest will include impact on patient safety and the broader effects on health systems. Quality of the randomised quantitative studies will be assessed using Cochrane Risk of Bias Tool. Non-randomised papers will be evaluated with the Risk of Bias In Non-Randomised Studies—of Interventions tool. Drummond’s Checklist will be used for publications pertaining to economic evaluation. The National Institute for Health and Care Excellence quality appraisal checklist will be used to assess qualitative studies. A narrative synthesis will be conducted for included studies, and the body of evidence will be summarised in a summary of findings table. Ethics and dissemination This review will summarise published studies with non-identifiable data and, thus, does not require ethical approval. Findings will be disseminated through preprints, open access peer-reviewed publications, and conference presentations. PROSPERO registration number CRD42020209285.
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Resumen Objetivo Se realiza un estudio observacional antes y después para valorar el efecto de la consulta virtual (eConsulta) sobre la frecuentación posterior que realiza el paciente a su centro de atención primaria una vez ha realizado su primera consulta virtual. Emplazamiento Población asignada de los Centros de Atención Primaria Masnou-Alella y Ocata-Teià del Institut Català de la Salut. Participantes Se realiza un muestreo aleatorizado y se comparan 329 pacientes que realizaron eConsultas respecto de 329 pacientes estadísticamente similares en edad, sexo y complejidad médica que no realizaron ninguna eConsulta. Mediciones principales Se midieron las visitas realizadas con medicina primaria y enfermería de su equipo, tanto presenciales, telefónicas y eConsultas, durante el periodo de estudio. Resultados Los pacientes que realizaron consultas virtuales mostraron una frecuentación previa en la atención primaria mayor que aquellos que no realizaron eConsultas (4,44 visitas médicas/año versus 3,11). Tras el uso de la eConsulta, después de un año de seguimiento, su frecuentación se redujo hasta niveles del grupo control (3,16 visitas médicas/año versus 3,00). Tras la primera visita virtual, los pacientes redujeron las visitas presenciales en un 28,7%. Conclusiones La eConsulta podría ser una herramienta eficaz para dar respuesta a las necesidades de los pacientes que no requieran de una visita presencial, en especial en los pacientes más frecuentadores.
In recent years we have seen a dramatic increase in health‐related data resulting in enormous data sets and sources, typically described as big data. Within the National Institutes of Health, big data refers to the complexity, challenges, and new opportunities presented by the combined analysis of diverse, multimodal, and unstructured data, usually with data volumes greater than one terabyte. Big data science, as it applies to precision medicine, is the generation and storage of large amounts of data from biospecimens, health records, medical imaging, and sensors from which disease‐specific factors, patterns, and associations can be computationally identified and used to generate insights for clinical care, decision making, and treatment. In the broad sense, it includes electronic health records, biologic data (genomics, proteomics, metabolomics), environmental and lifestyle data, and data from wearable technology and mobile phone applications. This chapter will discuss the foundations of big data, big data analytics, and opportunities for conducting health disparities research.
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The National Committee for Quality Assurance's 2006 report on the per- formance of U.S. health plans found overall improvement in HEDIS clinical quality measures for those plans that collect and publicly report performance data. Improve- ments, moreover, were broad-based.There are several lessons for those pursuing high performance of the U.S. health system as a whole. Most importantly, the results show there is hope; performance on some HEDIS measures is now approaching 100 percent. Diffusion of measurement has been slow, but steady.The nation needs more and bet- ter measures of performance, mechanisms for setting standards of performance, and tools, such as performance-based contracts, for ensuring that improvement occurs. * * * * *
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MyChart is one of the new, innovative features of Kaiser Permanente (KP) HealthConnect—the comprehensive, integrated, organizational, and personal electronic health and medical record. MyChart, an Epic Systems Corporation (Verona, WI) product, is a secure member Web site where registered patients can view portions of their medical record, and exchange secure messages with their primary care physician (PCP) and other recently visited clinicians. The KP Northwest (KPNW) Region, in Portland, Oregon, was the first KP Region to implement MyChart. Starting in late 2002, KPNW initiated a pilot project of MyChart as a stand-alone Web address in two medical offices.1 KPNW named this feature Personal Health Link (PHL). By early 2005, all adult primary care physicians and affiliated clinicians (both groups are PCPs in this paper) were trained and set up to use PHL. Patients who registered for PHL could send secure e-mail messages directly to their primary care clinician, incurring no copayment or fees. MyChart is now available to KP patients in all Regions, except Ohio, through KP HealthConnect online at
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This study examined the relationship between access and use of primary care physicians as sources of first contact and continuity with the medical system. Data from the 1987 National Medical expenditure Survey were used to examine the effects of access on use of primary care physicians as sources of first contact for new episodes of care (by logistic regression) and as sources of continuity for all ambulatory visits (by multi-variate linear regression). No after-hours care, longer office waits, and longer travel times reduced the chances of a first-contact visit with a primary care physician for acute health problems. Longer appointment waits, no insurance, and no after-hours care were associated with lower levels of continuity. Generalists provided more first-contact care than specialists acting as primary care physicians, largely because of their more accessible practices. These data provide support for the linkage between access and care seeking with primary care physicians.
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To determine whether paperless medical records contained less information than paper based medical records and whether that information was harder to retrieve. Cross sectional study with review of medical records and interviews with general practitioners. 25 general practices in Trent region. 53 British general practitioners (25 using paperless records and 28 using paper based records) who each provided records of 10 consultations. Content of a sample of records and doctor recall of consultations for which paperless or paper based records had been made. Compared with paper based records, more paperless records were fully understandable (89.2% v 69.9%, P=0.0001) and fully legible (100% v 64.3%, P < 0.0001). Paperless records were significantly more likely to have at least one diagnosis recorded (48.2% v 33.2%, P=0.05), to record that advice had been given (23.7% vs 10.7%, P=0.017), and, when a referral had been made, were more likely to contain details of the specialty (77.4% v 59.5%, P=0.03). When a prescription had been issued, paperless records were more likely to specify the drug dose (86.6% v 66.2%, P=0.005). Paperless records contained significantly more words, abbreviations, and symbols (P < 0.01 for all). At doctor interview, there was no difference between the groups for the proportion of patients or consultations that could be recalled. Doctors using paperless records were able to recall more advice given to patients (38.6% v 26.8%, P=0.03). We found no evidence to support our hypotheses that paperless records would be truncated and contain more local abbreviations; and that the absence of writing would decrease subsequent recall. Conversely we found that the paperless records compared favourably with manual records.
Specialty care has been used to manage individual patients at the discretion of generalists but not to drive improvements at the population level. Observational longitudinal study. Kaiser Permanente Hawaii, with more than 10,000 members with documented chronic kidney disease. Rate of late referrals to nephrology care, defined as occurring within four months of end stage renal disease and the proportions of patients starting haemodialysis with a mature arteriovenous fistula and starting dialysis in the outpatient setting. Risk stratification of the entire population and unsolicited consultations provided by nephrologists to generalists, based on patients' risk level, enabled by an electronic population management database. Between 2004 and 2008, the proportion of referrals occurring within four months of onset of end stage renal disease dropped from 37 of 116 (32%) to 10 of 84 (12%), P=0.001. The proportion of patients starting haemodialysis with a mature arteriovenous fistula increased from 19 of 108 (18%) to 27 of 76 (36%), P=0.006. The proportion of patients who started haemodialysis as outpatients increased from 39 of 113 (35%) to 47 of 84 (56%), P=0.003. Turning the traditional referral system on its head by providing unsolicited, risk driven nephrology consultations is an effective strategy for increasing the quality of medical management of patients with chronic kidney disease in the primary care setting and improving the cost effective use of nephrology services. This approach may be broadly applicable to other specialty areas.
To determine 1) the electronic mail (e-mail) capabilities of families, general pediatricians (GPs), and subspecialty pediatricians (SPs) from an integrated pediatric health care delivery system and 2) the knowledge base and attitudes of these groups regarding the potential issues involved in using e-mail for physician-patient communication. Parents were interviewed in the offices of participating practices using a standardized survey tool. Pediatricians and staff were interviewed using a separate instrument. The data were entered into a database for analysis. A total of 325 parents and 37 physicians were interviewed. Fifty-seven percent of the 161 parents who were interviewed at the GP offices and 66% of the 164 families that were interviewed at SP offices had access to e-mail. Parents aged 31 to 40 years were significantly more likely to have access to e-mail than parents of other age groups. Access to e-mail increased with family income and parental education. Most (74%) parents who were interviewed expressed interest in using e-mail to contact their child's physician/physician's office for several purposes, including getting information or test results, scheduling appointments, and/or discussing a particular symptom. Although both groups of parents expressed concerns about confidentiality, parents at the GP offices were significantly more concerned (median(GP) = 95 vs median(SP) = 70). Seventy-four percent of GPs and 100% of SPs had access to e-mail; however, 79% did not want to use e-mail for physician-patient communication, citing concerns about confidentiality and the time demands that patient e-mail might engender. The majority of parents and pediatricians at both general and subspecialty pediatric offices are capable of communicating electronically. Parents and pediatricians are aware of the issues surrounding e-mail use for patient communication. Most parents express an interest in using e-mail for patient-physician communications, whereas most physicians are opposed to this practice.
Timeliness, one of the Institute of Medicine's six aims for improving the quality of health care, is an important yet understudied aspect of health care. It has been well documented as a factor influencing satisfaction in many other service industries but not as frequently in health care, especially outside of the emergency department. This article examines current trends with wait times and their effect on overall satisfaction with care in physician's offices and outpatient test and treatment facilities offering both analysis of the current situation and recommendations for improvement in the future.
Iatrogenic injuries related to medications are common, costly, and clinically significant. Computerized physician order entry (CPOE) and clinical decision support systems (CDSSs) may reduce medication error rates. We identified trials that evaluated the effects of CPOE and CDSSs on medication safety by electronically searching MEDLINE and the Cochrane Library and by manually searching the bibliographies of retrieved articles. Studies were included for systematic review if the design was a randomized controlled trial, a nonrandomized controlled trial, or an observational study with controls and if the measured outcomes were clinical (eg, adverse drug events) or surrogate (eg, medication errors) markers. Two reviewers extracted all the data. Discussion resolved any disagreements. Five trials assessing CPOE and 7 assessing isolated CDSSs met the criteria. Of the CPOE studies, 2 demonstrated a marked decrease in the serious medication error rate, 1 an improvement in corollary orders, 1 an improvement in 5 prescribing behaviors, and 1 an improvement in nephrotoxic drug dose and frequency. Of the 7 studies evaluating isolated CDSSs, 3 demonstrated statistically significant improvements in antibiotic-associated medication errors or adverse drug events and 1 an improvement in theophylline-associated medication errors. The remaining 3 studies had nonsignificant results. Use of CPOE and isolated CDSSs can substantially reduce medication error rates, but most studies have not been powered to detect differences in adverse drug events and have evaluated a small number of "homegrown" systems. Research is needed to evaluate commercial systems, to compare the various applications, to identify key components of applications, and to identify factors related to successful implementation of these systems.
Patient access to their electronic health care record (EHR) and Web-based communication between patients and providers can potentially improve the quality of health care, but little is known about patients' attitudes toward this combined electronic access. The objective of our study was to evaluate patients' values and perceptions regarding Web-based communication with their primary care providers in the context of access to their electronic health care record. We conducted an online survey of 4,282 members of the Geisinger Health System who are registered users of an application (MyChart) that allows patients to communicate electronically with their providers and view selected portions of their EHR. To supplement the survey, we also conducted focus groups with 25 patients who were using the system and conducted one-on-one interviews with ten primary care clinicians. We collected and analyzed data on user satisfaction, ease of use, communication preferences, and the completeness and accuracy of the patient EHR. A total of 4,282 registered patient EHR users were invited to participate in the survey; 1,421 users (33%) completed the survey, 60% of them female. The age distribution of users was as follows: 18 to 30 (5%), 31 to 45 (24%), 46 to 64 (54%), 65 and older (16%). Using a continuous scale from 1 to 100, the majority of users indicated that the system was easy to use (mean scores ranged from 78 to 85) and that their medical record information was complete, accurate, and understandable (mean scores ranged from 65 to 85). Only a minority of users was concerned about the confidentiality of their information or about seeing abnormal test results after receiving only an explanatory electronic message from their provider. Patients preferred e-mail communication for some interactions (e.g., requesting prescription renewals, obtaining general medical information), whereas they preferred in-person communication for others (e.g., getting treatment instructions). Telephone or written communication was never their preferred communication channel. In contrast, physicians were more likely to prefer telephone communication and less likely to prefer e-mail communication. Patients' attitudes about the use of Web messaging and online access to their EHR were mostly positive. Patients were satisfied that their medical information was complete and accurate. A minority of patients was mildly concerned about the confidentiality and privacy of their information and about learning of abnormal test results electronically. Clinicians were less positive about using electronic communication than their patients. Patients and clinicians differed substantially regarding their preferred means of communication for different types of interactions.