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Effect of electronic patient record use on mortality in End Stage Renal Disease, a model chronic disease: retrospective analysis of 9 years of prospectively collected data.

Pollak VE, Lorch JA - BMC Med Inform Decis Mak (2007)

Bottom Line: Year by year mortality, hospital admissions, and staffing were analyzed, and the data were compared with national data compiled by the United States Renal Data System.Analyzed by calendar year after electronic patient record implementation, mortality decreased strikingly.That the population studied has many underlying diseases affecting all organ systems suggests that the electronic patient record design may enable application to many fields of medical practice.

View Article: PubMed Central - HTML - PubMed

Affiliation: MIQS Inc,, 2100 Central Avenue, Suite 201, Boulder, Colorado 80301, USA. vpollak@miqs.com

ABSTRACT

Background: In chronic disease, health information technology promises but has yet to demonstrate improved outcomes and decreased costs. The main aim of the study was to determine the effects on mortality and cost of an electronic patient record used in daily patient care in a model chronic disease, End Stage Renal Disease, treated by chronic maintenance hemodialysis. Dialysis treatment is highly regulated, and near uniform in treatment modalities and drugs used.

Methods: The particular electronic patient record, patient-centered and extensively coded, was used first in patient care in 3 dialysis units in New York, NY in 1998, 1999, and 2000. All data were stored "live"; none were archived. By December 31, 2006, the patients had been treated by maintenance hemodialysis for a total of 3924 years. A retrospective analysis was made using query tools embedded in the software. The United States Renal Data System dialysis population served as controls. In all there were 1790 patients, with many underlying primary diseases and multiple comorbid conditions affecting many organ systems. Year by year mortality, hospital admissions, and staffing were analyzed, and the data were compared with national data compiled by the United States Renal Data System.

Results: Analyzed by calendar year after electronic patient record implementation, mortality decreased strikingly. In years 3-9 mortality was lower than in years 1-2 by 23%, 48%, and 34% in the 3 units, and was 37%, 37%, and 35% less than that reported by the United States Renal Data System. Clinical staffing was 25% fewer per 100 patients than the national average, thereby lowering costs.

Conclusion: To our knowledge, this is the first demonstration that an electronic patient record, albeit of particular design, can have a favorable effect on outcomes and cost in chronic disease. That the population studied has many underlying diseases affecting all organ systems suggests that the electronic patient record design may enable application to many fields of medical practice.

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Mortality rate, by years of electronic patient record deployment, in dialysis Units A, B, and C. The mortality rate is compared with that reported by USRDS (horizontal line).
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Figure 4: Mortality rate, by years of electronic patient record deployment, in dialysis Units A, B, and C. The mortality rate is compared with that reported by USRDS (horizontal line).

Mentions: The effect of year-to-year variation may be expected to be less when the results are recapitulated in periods of two or more successive years. Mortality for years 1–2, 3–4, and 5–9 of EPR deployment is summarized in Figure 4. In Unit A, mortality in years 3–4 was 198 per 1000 years, similar to that in years 1–2. In years 5–9, mortality was 129 per 1000 years, a reduction of 35%. In Unit B, mortality was 44% lower in years 3–4 than in years 1–2, and 49% lower in years 5–8. In Unit C mortality was 36% lower in years 3–4 than in years 1–2, and 32% lower in years 5–7. By contrast, the contemporaneous USRDS mortality remained constant around 237 per 1000 years from 1998 to 2003, and decreased slightly to 232 and 229 per 1000 years in 2004 and 2005.


Effect of electronic patient record use on mortality in End Stage Renal Disease, a model chronic disease: retrospective analysis of 9 years of prospectively collected data.

Pollak VE, Lorch JA - BMC Med Inform Decis Mak (2007)

Mortality rate, by years of electronic patient record deployment, in dialysis Units A, B, and C. The mortality rate is compared with that reported by USRDS (horizontal line).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2238736&req=5

Figure 4: Mortality rate, by years of electronic patient record deployment, in dialysis Units A, B, and C. The mortality rate is compared with that reported by USRDS (horizontal line).
Mentions: The effect of year-to-year variation may be expected to be less when the results are recapitulated in periods of two or more successive years. Mortality for years 1–2, 3–4, and 5–9 of EPR deployment is summarized in Figure 4. In Unit A, mortality in years 3–4 was 198 per 1000 years, similar to that in years 1–2. In years 5–9, mortality was 129 per 1000 years, a reduction of 35%. In Unit B, mortality was 44% lower in years 3–4 than in years 1–2, and 49% lower in years 5–8. In Unit C mortality was 36% lower in years 3–4 than in years 1–2, and 32% lower in years 5–7. By contrast, the contemporaneous USRDS mortality remained constant around 237 per 1000 years from 1998 to 2003, and decreased slightly to 232 and 229 per 1000 years in 2004 and 2005.

Bottom Line: Year by year mortality, hospital admissions, and staffing were analyzed, and the data were compared with national data compiled by the United States Renal Data System.Analyzed by calendar year after electronic patient record implementation, mortality decreased strikingly.That the population studied has many underlying diseases affecting all organ systems suggests that the electronic patient record design may enable application to many fields of medical practice.

View Article: PubMed Central - HTML - PubMed

Affiliation: MIQS Inc,, 2100 Central Avenue, Suite 201, Boulder, Colorado 80301, USA. vpollak@miqs.com

ABSTRACT

Background: In chronic disease, health information technology promises but has yet to demonstrate improved outcomes and decreased costs. The main aim of the study was to determine the effects on mortality and cost of an electronic patient record used in daily patient care in a model chronic disease, End Stage Renal Disease, treated by chronic maintenance hemodialysis. Dialysis treatment is highly regulated, and near uniform in treatment modalities and drugs used.

Methods: The particular electronic patient record, patient-centered and extensively coded, was used first in patient care in 3 dialysis units in New York, NY in 1998, 1999, and 2000. All data were stored "live"; none were archived. By December 31, 2006, the patients had been treated by maintenance hemodialysis for a total of 3924 years. A retrospective analysis was made using query tools embedded in the software. The United States Renal Data System dialysis population served as controls. In all there were 1790 patients, with many underlying primary diseases and multiple comorbid conditions affecting many organ systems. Year by year mortality, hospital admissions, and staffing were analyzed, and the data were compared with national data compiled by the United States Renal Data System.

Results: Analyzed by calendar year after electronic patient record implementation, mortality decreased strikingly. In years 3-9 mortality was lower than in years 1-2 by 23%, 48%, and 34% in the 3 units, and was 37%, 37%, and 35% less than that reported by the United States Renal Data System. Clinical staffing was 25% fewer per 100 patients than the national average, thereby lowering costs.

Conclusion: To our knowledge, this is the first demonstration that an electronic patient record, albeit of particular design, can have a favorable effect on outcomes and cost in chronic disease. That the population studied has many underlying diseases affecting all organ systems suggests that the electronic patient record design may enable application to many fields of medical practice.

Show MeSH
Related in: MedlinePlus