Glosario eSalud | eHealth Glossary


Glosario sobre eSalud | eHealth Glossary

Navegue por el glosario usando este índice.

Especial | A | B | C | D | E | F | G | H | I | J | K | L | M | N | Ñ | O | P | Q | R | S | T | U | V | W | X | Y | Z | TODAS

Página: (Anterior)   1  2  3  4  5  6  7  8  9  10  ...  38  (Siguiente)
  TODAS

A

Imagen de System Administrator

As FHIR Matures, Healthcare Interoperability Comes into Focus

de System Administrator - miércoles, 12 de abril de 2017, 14:28
 

Como FHIR Madura, la Interoperabilidad en Salud Entra en el Foco

As FHIR Matures, Healthcare Interoperability Comes into Focus

por Jennifer Bresnick

"FHIR is an opportunity to take data into places that we never thought possible," says HL7 CEO Charles Jaffe, but only if developers can keep on the right side of the hype.

The Fast Healthcare Interoperability Resource, better known as FHIR, has quickly seared itself into the consciousness of the health IT industry, becoming one of the most promising methodologies for open, seamless data exchange.

In just a few short years, the internet-based interoperability standard has popped up on IT developers' must-have list, capturing the attention of everyone from first-time startups to some of the heaviest hitters in the electronic health record community.

While every industry has more failed standards than successes, and only time will tell if this go-around will be any different, the excitement around FHIR seems justly deserved.

FHIR is one of the first efforts that is offering a new path forward firmly backed by both the private and public sectors without regulatory coercion. And it's one of the first approaches that truly aligns with the way technology in other sectors has been developing.

At the HL7 FHIR Value-Based Care Summit this week in Chicago, that excitement was palpable.

FHIR is making the leap from a developer-centric technical framework to one that empowers real-world implementers, said HL7 International CEO Charles Jaffe, MD, PhD, turning healthcare big data into "the change vehicle it has always promised to be."

"This is where the real change happens," he said. "Carequality and Commonwell have committed to developing a FHIR-based platform. In Silicon Valley, in the public space, and all around the world, there are companies that have committed significant investments to this."

"This is an opportunity to take data into places that we never thought possible."


What Healthcare IT Users Don't Really Need to Know About FHIR


It may be tempting to dismiss a room full of FHIR evangelists as little more than a factory for meaningless hype, but the enthusiasm was strongly tempered with a recognition that FHIR is still evolving, and will continue to do so for the foreseeable future.

"Release 3 is an important milestone that will enable a host of functionalities that weren't present in previous iterations," said Jaffe. "But like all standards, it isn't going to be useful if it doesn't change. FHIR will be evolutionary as the world of analytics blossoms."

The world of big data analytics is blooming more quickly than many healthcare providers can cope with. Big data is now a fact of life, and the ability to move information back and forth wherever it needs to go has become a clinical and financial imperative.

However, "the need for data has outpaced the industry's ability to deliver it," said Mike Baillie, Vice President of Optum Data eXchange at OptumInsight.

"We want to get to the point where we can connect once and then use that data many times," he said. "We're not there yet. If we're going to do that, we need to get the incentives in the right places, and we need to combine the assets of multiple players – that means payers, providers, and developers working together to improve this fragmented data landscape we're dealing with."

Data siloes aren't a new problem, but they aren't an intractable one, either. And they might not be the only thing going wrong with interoperability, says Shahid Shah, Entrepreneur in Residence at the AHIP Innovation Lab.

"There is no interoperability crisis," said Shah, who is also Co-founder and CEO of Netspective Communications. "There are plenty of people supplying interoperability services. The real crisis is that we're not managing and coordinating the demand for interoperability with the huge amount of available supply."


Can Application Programming Interfaces Inspire a Better EHR?


When end-users, including providers, patients, and researchers, don't have access to the data they need to make better decisions, they end up on the wrong end of the "information asymmetry" equation, said Shah.

"In the payer-provider, pharma-payer, or patient-provider relationship, there are some people who have more data than others," he explained. "When you have data inequalities, the party in power can charge more money for the things the other players don't know."

"FHIR can be a way to reduce information asymmetry. It's the developer's job to make sure that whatever they're doing with FHIR ends up balancing that unequal data access situation. You have to match development to real, existing, applicable use cases if you want to get tangible value out of your efforts."

The widespread emphasis on tying FHIR to real-world uses is one reason why the standard has thus far avoided the trap of getting too carried away by its own early successes.

"Never embark on a use case before figuring out how it's going to bring dollars back into the system or measurably improve clinical outcomes," Shah warned.

"If you have a solid business case, then you know that your management is going to have a reason to invest. The business case can highlight the priority of doing this, and that's how you grow adoption."


Why Health Data Interoperability is Setting EHR Vendors on FHIR


If FHIR can stay anchored in its utility to the ultimate end user – the patient – then every stakeholder along the way can benefit from adopting FHIR-based tools, added Baillie.

"The value-based care movement is putting some big dollars on the line for organizations that are taking on risk," he said. "There is a lot of money attached to the ability to understand data and use it to raise the quality of care."

"Small improvements can snowball into major financial gains, but we won't get there unless we figure out how to build the pipelines that can serve up patient data when and where it's needed, with all the right protections in place."

FHIR's maturity doesn't just show itself in the number of public releases or how long it has been at the forefront of the industry's thoughts. It is becoming mature because of the recognition that is perennially unfinished, which highlights both its limitless potential and the unending need to commit to making it work.

"There's a real opportunity to have these worlds come together," said Baillie. "One of the things that the payer industry has learned when trying to use claims data for value-based care is that straight and narrow data pathways just aren't going to cut it. Risk sharing requires that more people access the data, and that means we need to develop new ways to share information so that we're all speaking the same language."

"We all want to take those lessons and make something good out of them. FHIR is one way that we can do that."

Dig Deeper

Related Articles

Related Resources

Link: http://healthitanalytics.com

B

Imagen de System Administrator

Bajar la presión arterial, ¿hay un límite?

de System Administrator - sábado, 30 de agosto de 2014, 21:24
 
Mortalidad y nefropatía terminal 

Bajar la presión arterial, ¿hay un límite?

El tratamiento de la hipertensión disminuye la morbimortalidad, pero aún no está definido cuál es la presión óptima que se debe alcanzar. La PAS superior o inferior a 130 - 139 mm Hg y la PAD superior o inferior a 60 - 79 mm Hg se asocian con peor evolución en pacientes hipertensos que reciben tratamiento.
Autor: Sim JJ, Shi J, Kovesdy CP et al Fuente: Journal of the American College of Cardiology vol. 6 4, no. 6, 2 0 1 4 Impact of Achieved Blood Pressures on Mortality Risk and End-Stage Renal Disease Among a Large, Diverse Hypertension Population
Fuente: IntraMed | Traducción y resumen objetivo: Dr. Ricardo Ferreira

Intraducción

A medida que el tratamiento y la normalización de la hipertensión arterial (HTA) continúan mejorando, los debates se centraron sobre la presión más apropiada en pacientes hipertensos tratados, específicamente en relación con el grado de intensidad con que se debe tratar su presión arterial (PA).

Se supone que hay una relación lineal entre la PA y el riesgo vascular y de mortalidad. Las PA más bajas en todos los grupos etarios se asociaron con los mayores beneficios de morbilidad y supervivencia. Estas observaciones llevaron a la conclusión de que el descenso de la PA a lo largo de ese eje lineal generará la disminución proporcional del riesgo.

La percepción es similar para el riesgo de insuficiencia renal. Se demostraron reducciones del riesgo significativas en estudios intervencionistas que lograron el descenso de la PA en pacientes con HTA grave. Sin embargo, no se han mostrado beneficios con el descenso tensional intensivo que, incluso, puede ser contraproducente. En poblaciones de alto riesgo, como aquéllas con diabetes mellitus (DM) y nefropatía crónica, las intervenciones para disminuir la PA por debajo de los niveles deseados habituales no demostraron mejoras en los resultados.

En realidad, el descenso intensivo se asoció con peores resultados, lo que sugiere una curva en forma de J. Esta curva no lineal es similar a la observada en otros factores de riesgo cardiovascular. De manera que para la población general con HTA, la relación entre el tratamiento de la HTA y la evolución del paciente no está bien definida.

Los autores estudiaron una población que recibía tratamiento médico para la HTA a fin de evaluar la PA lograda y el riesgo ulterior de mortalidad y de nefropatía terminal (NPT). 

Métodos

Se efectuó un estudio de cohortes retrospectivo en pacientes del sistema de salud Kaiser Permanente Southern California, (KPSC) entre enero de 2006 y diciembre de 2010. Este sistema se compone de 14 centros médicos y más de 200 consultorios médicos. La población que se atiende es de gran diversidad étnica y socioeconómica.

Se estudió a pacientes hipertensos tratados mayores de 18 años.

Tratamiento de la HTA en Kaiser Permanente. Desde 2005, KPSC dispone de un algoritmo simplificado para el tratamiento de la HTA. La mayoría de los médicos de la institución siguen este algoritmo. Durante el período del estudio, las tasas de descenso de la HTA en la población del KPSC fueron del 65% al 80%.

Criterios de valoración. El criterio principal de valoración fue una combinación de mortalidad o NPT. 
Los criterios secundarios fueron la NPT y la mortalidad por separado como riesgos que compiten y, en los análisis estratificados de aquéllos con diabetes o sin ella, la edad < 70 o ≥ 70 años y las puntuaciones CCI (Índice de comorbilidades de Charlson).

Se emplearon los modelos de regresión de riesgos proporcionales de Cox para evaluar los riesgos (índices de riesgo) para mortalidad y NPT entre diferentes clases de PA con estratificación para diabetes mellitus y ancianidad o sin ella.

Los valores de 130 - 139 y 80 - 89 mm Hg se emplearon como referencia para la PA sistólica (PAS) y la PA diastólica (PAD), respectivamente.

Resultados

Se estudiaron 398.419 pacientes hipertensos que recibían tratamiento. La PA media fue 131/73 mm Hg con desvíos estándar para la PAS (11 mm Hg) y la PAD (8 mm Hg), respectivamente.

En los pacientes que murieron, la PAS media disminuyó 7 mm Hg durante los 60 días previos a la muerte (124 vs. 131 mm Hg [p < 0,01]). Las diferencias en la PAD no fueron tan pronunciadas, con  disminución de 3 mm Hg (70 mm Hg antes y 67 mm Hg dentro de los 60 días de la mortalidad [p < 0,01]).

Se consideró que el 83% de la población con HTA había normalizado su PA (< 140 mm Hg) durante el período de observación. Se dispuso de información sobre el índice de masa corporal (IMC) en el 99% de la cohorte del estudio y se consideró obeso al 43% de los participantes.

La frecuencia de enfermedades concomitantes (comorbilidades) fue la siguiente: DM 30%; cardiopatía isquémica 19% y enfermedad cerebrovascular 8%. La media de la creatininemia y de la filtración glomerular estimada (FGe) fue 1,0 mg/dl and 74 ml/min/1,73 m2, respectivamente. En total, el 24% de la población tuvo una FGe inferior a 60 ml/min/1,73 m2.

Los medicamentos administrados fueron en general los de las recomendaciones del KPSC: diuréticos (80%), inhibidores de la enzima convertidora de angiotensina (70%), beta-bloqueantes (44%) y bloqueantes de los canales de calcio (37%).

Los grupos con PAS más baja y más alta tuvieron las mayores tasas de mortalidad

Tasas de mortalidad o NPT. Un total de 28919 personas (el 7,3%) en la cohorte alcanzaron el criterio de valoración compuesto de mortalidad o NPT. La media y la mediana de seguimiento fueron de 4,0 y 4,5 años, respectivamente.

Los grupos con PAS más baja y más alta tuvieron las mayores tasas de mortalidad/NPT (22,9% y 15,7%).

Si se toman los criterios de valoración por separado, se produjo mortalidad en 25182 (6,3%) y NPT en 4957 pacientes (1,2%). Las tasas de mortalidad también fueron mayores en los grupos de PAS más baja y más alta. Las tasas de NPT parecieron aumentar con las PAS más altas (6,9% de los pacientes ≥ 170 mm Hg). En cambio, no pareció haber un aumento desproporcionado de la NPT en los grupos con la PAS más baja (3,4% de los pacientes < 110 mm Hg).

Análisis estratificados. Los índices de riesgo (IR) para mortalidad/NPT en pacientes con DM, en relación con pacientes no diabéticos se desplazaron a las PA más bajas y tuvieron mejor evolución. Las PA más bajas en pacientes con DM fueron 131 y 69 mm Hg para la PAS y la PAD, respectivamente, mientras que en los pacientes no diabéticos fueron de 142 y 73 mm Hg.

Cuando se evaluó sólo la mortalidad, los pacientes no diabéticos tuvieron mayor supervivencia en los extremos superiores de PA que la subpoblación diabética. Para los análisis de la NPT sola, las personas con DM, en relación con los pacientes no diabéticos, tuvieron mejor evolución en los extremos inferiores de PA. Sin embargo, las personas con DM evolucionaron peor con la PA más alta que aquéllos sin DM.

Edad. Las PA más bajas estimadas para mortalidad/ NPT en personas  ≥ 70 años fueron 140 y 70 mm Hg para la PAS y la PAD, respectivamente, mientras que en pacientes más jóvenes las PA más bajas fueron 133 y 76 mm Hg. Para el riesgo de NPT sola, el grupo < 70 años evolucionó mejor con valores más bajos de PA en relación con aquéllos de ≥ 70 años, pero fueron más susceptibles con la PA más alta.

Enfermedad cardiovascular previa. Las interacciones entre cardiopatía isquémica y PA fueron significativas para la mortalidad (p < 0,001) y la combinación de mortalidad/ NPT (p < 0,001). Las interacciones entre enfermedad cerebrovascular y PA fueron significativas sólo para mortalidad/ NPT ESRD (p = 0,02). Se efectuaron IR para los criterios de valoración mortalidad/ NPT en aquéllos con cardiopatía isquémica previa y sin ella y también en aquéllos con enfermedad cerebrovascular y sin ella. En relación con los pacientes sin enfermedad cardiovascular y PAS 130 - 139 mm Hg, los IR para mortalidad/ NPT fueron:

    • en los pacientes con cardiopatía isquémica previa: 4,19, 2,21, 1,43, 1,36, 2,03, 3,73, 4,38y 7,69; 
    • en los pacientes con enfermedad cerebrovascular previa: 6,18, 2,33, 1,63, 1,44, 2,06, 2,74, 4,05 y 4,77 para PAS <110, 110 - 119, 120 - 129, 130 - 139, 140 - 149, 150 - 159, 160 – 169 y >169 mm Hg, respectivamente.

Nefropatía crónica. Cada disminución de 10 ml/min/1,73 m2 en la FGe se asoció con un IR de mortalidad/ NPT de 1,08 (IC del 95%: 1,07 – 1,09).

¿Cuál es el nivel óptimo de presión arterial?

 

Discusión

Este estudio de observación de una cohorte grande y diversa de personas con HTA tratada médicamente demuestra que la PA lograda tanto en los límites superiores como en los inferiores se asocia con aumento del riesgo de mortalidad y de NPT.

Se observó una curva en U para el criterio de valoración compuesto de mortalidad/ NPT con PAS >139 y <130 mm Hg. Hubo aumentos graduales del riesgo en ambas direcciones. Las PAD < 60 y > 79 mm Hg también tuvieron mayor riesgo. Las PA más bajas asociadas con los mejores resultados fueron 137 mm Hg para la PAS y 71 mm Hg para la PAD. Las PAS y el riesgo de NPT solo mostraron una curva un poco en forma de J con menor riesgo con PAS de 110 - 139 mm Hg.

La población del estudio incluyó gran cantidad de pacientes diabéticos y de pacientes ≥ 70 años. Los análisis estratificados, tanto en la población con DM como en la de ≥70 años demostraron una curva de riesgo en U. En este estudio, los pacientes con DM tuvieron mejor evolución con PA más baja que los no diabéticos, pero su PAS óptima siguió en la gama de 130 - 139 mm Hg.

Históricamente la PA más baja se asoció con mejor supervivencia de la enfermedad vascular y con menor mortalidad. Estudios intervencionistas que lograron el descenso de la PA en poblaciones con HTA extrema demostraron mejoría significativa de la morbimortalidad en pacientes tanto con DM como sin ella. Esto generó iniciativas para aumentar la conciencia sobre la HTA y la implementación de estrategias para su descenso. Se hizo hincapié en que cuanto más baja la presión mejor sería la evolución del paciente. Esto no necesariamente se aplica a la población con HTA que recibe tratamiento.

La PA ideal en la población hipertensa no ha sido estudiada satisfactoriamente. Si bien la hipertensión es perjudicial, los beneficios del tratamiento se mostraron sobre todo cuando se logró una PAS >130 mm Hg. El tratamiento intensivo de la HTA para lograr presiones muy bajas puede tener consecuencias negativas. Varios estudios sugirieron peores resultados con el tratamiento para lograr un PA relativamente más baja, mientras que otros sugirieron que quizás no haya beneficios demostrados del tratamiento de los pacientes con HTA leve salvo que tengan evidencia de daño orgánico. Las recomendaciones recientes de 2014 basadas en la evidencia para el tratamiento de la HTA sugieren PA y umbral para el tratamiento más altos en los pacientes con DM, nefropatía crónica y edad ≥60 años. 

Limitaciones del estudio. La PA lograda quizás no necesariamente refleje la PA que se deseaba con el tratamiento, sino que puede representar un biomarcador para una población más enferma. Un ejemplo de esta limitación es la frecuencia desproporcionada de cardiopatía isquémica a través de todos los valores de PA.

Las interacciones estudiadas entre la cardiopatía isquémica y la PA demostraron significación, lo que denota que la enfermedad cardiovascular prexistente puede afectar el IR. Sin embargo, en análisis separados de las poblaciones con enfermedad cardiovascular y sin ella, el IR a través de todos los valores de la PA continuó demostrando una curva en U.

La obesidad también fue muy frecuente en la población estudiada: el 43% tuvo un IMC ≥30 kg/m2. Esta cohorte también demostró una paradoja de la obesidad similar a la mencionada en el pasado en otras poblaciones de alto riesgo. La obesidad tuvo efecto protector y los que eran obesos tuvieron un IR de mortalidad/NPT de 0,85 (IC del 95%: 0,83 – 0,88).

Debido a que la PA disminuye hacia el final de la vida, la PA media durante el período de observación puede tener efectos de confusión, ya que quizás refleje los procesos que conducen a la NPT o a la muerte más que la PA actual tratada.

Otro factor de confusión es el efecto del tratamiento medicamentoso sobre la evolución. Las diferentes clases de medicamentos y la cantidad de los mismos pueden tener efectos pleiotrópicos además del efecto hipotensor. 
El sesgo de los médicos puede haber sido otra limitación, ya que los pacientes que ellos identificaron como más enfermos quizás hayan sido vistos con mayor frecuencia y tratados de manera más intensiva. 
A pesar de estas limitaciones, las fortalezas de este estudio son la gran población con HTA, con diversidad étnica y gran número de pacientes diabéticos y ancianos.


Conclusiones

Los autores hallaron que los pacientes hipertensos tratados, con PAS de 130 - 139 mm Hg y PAD de 60 - 79 mm Hg son los que tuvieron el riesgo más bajo de sufrir el criterio de valoración compuesto de mortalidad y NPT. Los pacientes con PA superior o inferior tuvieron mayor riesgode sufrir estos parámetros.

Mientras que las recomendaciones de los EEUU hacen hincapié en los límites superiores de los objetivos terapéuticos, es necesario tener en cuenta los posibles riesgos del tratamiento excesivo. Tanto el aumento como la suspensión de los medicamentos pueden ser apropiados para tener resultados óptimos en la población con HTA.

REFERENCIAS

1. Cutler JA, Sorlie PD, Wolz M, Thom T, Fields LE, Roccella EJ. Trends in hypertension prevalence, awareness, treatment, and control rates in United States adults between 1988-1994 and 1999- 2004. Hypertension 2008;52:818–27.
2. Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008. JAMA 2010; 303:2043–50.
3. Lewington S, Clarke R, Qizilbash N, Peto R, Collins R. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. Lancet 2002; 360: 1903–13.
4. Whelton PK, He J, Appel LJ, et al. Primary prevention of hypertension: clinical and public health advisory from The National High Blood Pressure Education Program. JAMA 2002; 288: 1882–8.
5. Klag MJ, Whelton PK, Randall BL, et al. Blood pressure and end-stage renal disease in men. N Engl J Med 1996; 334:13–8.
6. Group VACS. Effects of treatment on morbidity in hypertension. Results in patients with diastolic blood pressures averaging 115 through 129 mm Hg. JAMA 1967; 202:1028–34.
7. SHEP. Prevention of stroke by antihypertensive drug treatment in older persons with isolated systolic hypertension. Final results of the Systolic Hypertension in the Elderly Program (SHEP). SHEP Cooperative Research Group. JAMA 1991;265: 3255–64.
8. Turnbull F, Neal B, Ninomiya T, et al. Effects of different regimens to lower blood pressure on major cardiovascular events in older and younger adults: meta-analysis of randomised trials. BMJ 2008; 336:1121–3.
9. Group UPDS. Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. UK Prospective Diabetes Study Group. BMJ 1998; 317: 703–13.
10. Hansson L, Zanchetti A, Carruthers SG, et al. Effects of intensive blood-pressure lowering and low-dose aspirin in patients with hypertension: principal results of the Hypertension Optimal Treatment (HOT) randomised trial. HOT Study Group. Lancet 1998; 351:1755–62.
11. Julius S, Kjeldsen SE, Weber M, et al. Outcomes in hypertensive patients at high cardiovascular risk treated with regimens based on valsartan or amlodipine: the VALUE randomised trial. Lancet 2004; 363:2022–31.
12. Staessen JA, Fagard R, Thijs L, et al. Randomised double-blind comparison of placebo and active treatment for older patients with isolated systolic hypertension. The Systolic Hypertension in Europe (Syst-Eur) Trial Investigators. Lancet 1997; 350:757–64.
13. Staessen JA, Gasowski J, Wang JG, et al. Risks of untreated and treated isolated systolic hypertension in the elderly: meta-analysis of outcome trials. Lancet 2000; 355:865–72.
14. Cushman WC, Evans GW, Byington RP, et al. Effects of intensive blood-pressure control in type 2 diabetes mellitus. N Engl J Med 2010; 362: 1575–85.
15. Appel LJ, Wright JT Jr., Greene T, et al. Intensive blood-pressure control in hypertensive chronic kidney disease. N Engl J Med 2010; 363: 918–29.
16. JATOS Study Group. Principal results of the Japanese trial to assess optimal systolic blood pressure in elderly hypertensive patients (JATOS). Hypertens Res 2008; 31:2115–27.
17. Ogihara T, Saruta T, Rakugi H, et al. Target blood pressure for treatment of isolated systolic hypertension in the elderly: valsartan in elderly isolated systolic hypertension study. Hypertension 2010;56: 196–202.
18. Benavente OR, Coffey CS, Conwit R, et al. Blood-pressure targets in patients with recent lacunar stroke: the SPS3 randomised trial. Lancet 2013; 382:507–15.
19. Wright JT Jr., Bakris G, Greene T, et al. Effect of blood pressure lowering and antihypertensive drug class on progression of hypertensive kidney disease: results from the AASK trial. JAMA 2002; 288:2421–31.
20. Iseki K, Miyasato F, Tokuyama K, et al. Low diastolic blood pressure, hypoalbuminemia, and risk of death in a cohort of chronic hemodialysis patients. Kidney Int 1997; 51:1212–7.
21. Port FK, Hulbert-Shearon TE, Wolfe RA, et al. Predialysis blood pressure and mortality risk in a national sample of maintenance hemodialysis patients. Am J Kidney Dis 1999; 33:507–17.
22. Kovesdy CP, Bleyer AJ, Molnar MZ, et al. Blood Pressure and Mortality in U.S. Veterans With Chronic Kidney DiseaseA Cohort Study. Annals of Internal Medicine 2013; 159:233–42.
23. Yusuf S, Teo KK, Pogue J, et al. Telmisartan, ramipril, or both in patients at high risk for vascular events. N Engl J Med 2008; 358:1547–59.
24. Bangalore S, Messerli FH, Wun CC, et al. J-curve revisited: An analysis of blood pressure and cardiovascular events in the Treating to New Targets (TNT) Trial. Eur Heart J 2010; 31:2897–908.
25. Ruggenenti P, Perna A, Loriga G, et al. Blood pressure control for renoprotection in patients with non-diabetic chronic renal disease (REIN-2): multicentre, randomised controlled trial. Lancet 2005; 365:939–46.
26. Verma S, Gupta M, Holmes DT, et al. Plasma renin activity predicts cardiovascular mortality in the Heart Outcomes Prevention Evaluation (HOPE) study. Eur Heart J 2011; 32:2135–42.
27. Koebnick C, Langer-Gould AM, Gould MK, et al. Sociodemographic characteristics of members of a large, integrated health care system: comparison with US Census Bureau data. Perm J 2012; 16:37–41.
28. Bhandari SK, Pashayan S, Liu IL, et al. 25-hydroxyvitamin D levels and hypertension rates. J Clin Hypertens (Greenwich) 2011; 13:170–7.
29. Levey AS, Stevens LA, Schmid CH, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 2009; 150:604–12.
30. Sim JJ, Bhandari SK, Shi J, et al. Characteristics of resistant hypertension in a large, ethnically diverse hypertension population of an integrated health system. Mayo Clin Proc 2013; 88:1099–107.
31. Sim JJ, Bhandari SK, Shi J, et al. Plasma renin activity (PRA) levels and antihypertensive drug use in a large healthcare system. Am J Hypertens 2011; 25:379–88.
32. Sim JJ, Handler J, Jacobsen SJ, Kanter MH. Systemic implementation strategies to improve hypertension: the Kaiser Permanente Southern California experience. Can J Cardiol 2014; 30:544–52.
33. Go AS, Chertow GM, Fan D, MCCulloch CE, Hsu CY. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med 2004; 351:1296–305.
34. Zanchetti A. Blood pressure targets of antihypertensive treatment: up and down the J-shaped curve. Eur Heart J 2010; 31:2837–40.
35. Perry HM Jr., Davis BR, Price TR, et al. Effect of treating isolated systolic hypertension on the risk of developing various types and subtypes of stroke: the Systolic Hypertension in the Elderly Program (SHEP). JAMA 2000; 284:465–71.
36. Cooper-DeHoff RM, Gong Y, Handberg EM, et al. Tight blood pressure control and cardiovascular outcomes among hypertensive patients with diabetes and coronary artery disease. JAMA 2010; 304:61–8.
37. DeFelice A, Willard J, Lawrence J, et al. The risks associated with short-term placebo-controlled antihypertensive clinical trials: a descriptive metaanalysis. J Hum Hypertens 2008; 22:659–68.
38. Diao D, Wright JM, Cundiff DK, Gueyffier F. Pharmacotherapy for mild hypertension. Cochrane Database Syst Rev 2012; 8:CD006742.
39. James PA, Oparil S, Carter BL, et al. 2014 Evidence-based guideline for the management of high blood pressure in adults: report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014; 311:507–20.
40. Romero-Corral A, Montori VM, Somers VK, et al. Association of bodyweight with total mortality and with cardiovascular events in coronary artery disease: a systematic review of cohort studies. Lancet 2006; 368:666–78.
41. Diehr PH, Thielke SM, Newman AB, Hirsch C, Tracy R. Decline in health for older adults: five-year change in 13 key measures of standardized health. J Gerontol A Biol Sci Med Sci 2013;68:1059–67.

Imagen de System Administrator

Best Free Apps to Recommend to Patients

de System Administrator - martes, 14 de octubre de 2014, 11:36
 

Best Free Apps to Recommend to Patients

By Keith L. Martin

Alive ECG
• iTunes
• Google Play

Pill Reminder
 iTunes
• Google Play

iHealth BPM
• iTunes

Skype
• iTunes
• Google Play

MyFitnessPal
• iTunes
• Google Play

Lose It!
• iTunes
• Google Play

GoMeals
• iTunes
• Google Play

Omvana
 iTunes



SongPop
 iTunes
• Google Play

Fit Brains Trainer
• iTunes
• Google Play

To view the slides in PDF format, click here.

Link: http://www.physicianspractice.com

Imagen de System Administrator

Best Practices for Managing Archive Migrations

de System Administrator - viernes, 15 de agosto de 2014, 19:25
 

 

This white paper discusses a variety of challenges around migrating legacy archives and also offers a selection of choices and recommendations for improving the archive migration process.

Please read the attached whitepaper.

Imagen de System Administrator

Best Practices in Revenue Cycle: Preparing for Value-Based Care with Analytics

de System Administrator - miércoles, 23 de septiembre de 2015, 16:18
 

Best Practices in Revenue Cycle: Preparing for Value-Based Care with Analytics

The purpose of this guide is to shine a light on the current hospital revenue cycle management trends that have made an impact already and those that will play a role in the years to come. Hospitals and practices that are aware of these trends have a better chance of success by remaining ahead of the competition.

This guide comprises important insights from industry insiders and subject matter experts with ample experience navigating the healthcare revenue cycle efficiently and effectively.

Please read the attached whitepaper.

Imagen de System Administrator

Better Data Means Better Quality Healthcare

de System Administrator - domingo, 5 de julio de 2015, 20:09
 

Infographic: Better Data Means Better Quality Healthcare

by

Envision a future where everyone has access to affordable, personalized quality healthcare through sophisticated sensing technologies that put you in charge of your own health. Where sensors and devices recognize and measure your personal health information, provide insights and recommendations relevant to you and communicate that information to your physician.

The following infographic highlights the aim of the Nokia Sensing XChallenge: a whole new level of personalized, digital health information.

The Nokia Sensing XCHALLENGE is a $2.25 million global competition to accelerate the availability of hardware sensors and software sensing technology that individuals use to access, understand, and improve their health and well-being. Innovation in sensing is an important component to creating a means for appealing, usable, smarter digital health solutions.

Link: http://hitconsultant.net


Imagen de System Administrator

Beyond Games: Why VR Will Soon Be Vitally Important to Healthcare

de System Administrator - lunes, 24 de agosto de 2015, 22:56
 

Beyond Games: Why VR Will Soon Be Vitally Important to Healthcare

By Michael Aratow

Virtual reality (VR) is the new [old] buzzword [again], capturing the imagination of a new generation of early adopters, technologists and gamers. With its early roots in the 1950s simulation community, there have been decades of research, dedicated journals and conferences that have built a substantial VR knowledge base.

You can imagine how the current VR hype cycle must appear like a true déjà vu event for many VR veterans. But what’s different this time is that the technology is now within reach of the consumer…and almost out of reach of motion sickness.

And, there is a new benefactor: the gaming and entertainment market. The majority of recently created VR content is, therefore, made solely for the user’s enjoyment. However, though the global entertainment and media market is substantial (~$2 trillion), VR applications in other sectors are poised to have a much larger impact on our daily lives.

Consider the healthcare sector, which is a target rich environment for VR. Due to the variety and complexity of operational workflows in the medical field—only to be surpassed by the variety and complexity of human pathology—there are several opportunities for VR to create a significant impact: Education, simulation, diagnosis, treatment and behavior modification are major entry points.

Physical Therapy in Immersive Virtual Worlds

Physical therapy can be challenging, uncomfortable and boring. Compliance rates for home regimens can be extremely poor. Virtual reality will help enliven the process. My company, VRecover, is developing engaging, gamified, immersive environments with accurate motion tracking to help physical therapy patients keep up with treatment regimens and improve outcomes.

Much research has been conducted using motion capture devices to record a patient’s movements and map those movements onto a virtual avatar displayed on large screen monitors. Compared to traditional physical therapy, results have shown significant promise using this technique in patients with stroke, Parkinson’s disease and musculoskeletal injuries—but much less research has been performed in these settings using immersive VR with head-mounted displays (HMDs).

VRecover is betting that full immersion with presence will have an even more dramatic and beneficial effect on their recovery and become a critical modality for use by physical therapists. 

https://youtu.be/eUwmRJXk93E

Understanding Disease: A VR Experience Is Worth a Million Words

Patients have a varying understanding of their disease processes, and it is well known that after an encounter with a provider, patients can forget more than half of what they were discussing. While a picture is worth a thousand words, an immersive VR experience is worth a million.

Using immersive experiences to visualize their disease, patients can gain a significantly better understanding of the illness, allowing them to feel more empowered and therefore more willing to follow through with their treatment.

Understanding their condition is also critical for “informed consent.”

The process of educating a patient to the details of a treatment or procedure and its risks, benefits and alternatives, is required by law in all 50 states. It has been recognized as a critical and highly effective patient safety practice by the Agency for Healthcare Research and Quality and the National Quality Forum, both highly respected organizations which are influential in healthcare policy and practices.

Patients who are properly informed are more satisfied and willing to work with providers and less likely to file a malpractice claim. Informed consent is taken to a new level when the patient can actually see a simulated surgical procedure using 3D visualizations of their body from CT, MRI or PET scans.  When it is your body that you are looking at, rather than an impersonal 3D rendering or animation, you pay attention to every visual detail and hear every word of explanation. This is personalized medicine for imaging!

Again, the immersive experience is worth a million words—or the equivalent of a really long informed consent session!

Making Guided Imagery With VR

Guided imagery is a technique that can be used in many aspects of medicine, including medical conditions such as hypertension, treatments such as chemotherapy and radiation therapy for cancer, and psychological conditions such as anxiety and chronic pain. This technique directs a patient to imagine images that can promote healing and well being.  

The experience is obviously user dependent, with individuals realizing different levels of effectiveness based on their ability to concentrate on the visualization task. VR can not only accelerate the training for this mental exercise, but the experience now becomes more vivid, with content that can not only be personalized for the patient’s unique medical condition, but dynamically changed based on feedback.

Learning Anatomy With a Guided 3D Tour of the Body

Human anatomy is not an easy subject to master. Organic shapes arranged in complex and unintuitive configurations are difficult to comprehend, especially for those who have a hard time thinking in 3D.

Students won’t have to mentally struggle so much to reconstruct the spatial relationships of internal human anatomy in their mind using immersive VR.

Now, they will be able to view these relationships by freely moving to anywhere inside a virtual body and viewing from any angle. This will benefit not only the future surgeons of the world, but all providers, who will have better diagnostic and procedural competency through their improved understanding.

Surgeons Can Better Explore, Plan, and Practice Operations

No two people are alike, inside or out. Regardless of the experience of a surgeon, anatomic variability can at times be an interesting anomaly or a potential cause of complications.

The ability to understand an individual’s unique anatomic configuration from skin to bone can be a significant benefit to a surgeon, especially prior to a complex operation. Immersive VR will enable surgeons to explore their patient’s virtual body—reconstructed from their CT or MRI data—and plan or even practice difficult surgeries prior to the actual procedure.

This will lead to better outcomes through fewer complications, optimized surgical approaches and shorter operating times.

Powerful Ideas Finally Made Viable

While these use cases have been proposed or attempted in the past, they have been difficult to operationalize. But now with consumer access to quality VR, they can become viable solutions.

It is an exciting time to be involved in the VR renaissance. With almost monthly advances in displays, input devices, the software production pipeline or delivery platforms (VR can even be experienced through a web browser...check out WebVR)—there is much to learn and build upon the path blazed by the VR pioneers of the past. VR is not likely to return to the technology hibernation cave again!

Michael Aratow is CEO and co-Founder of VRecover, Chief Medical Information Officer at San Mateo Medical Center in San Mateo, CA, Board Certified in Emergency Medicine and Clinical Informatics and still practices Emergency Medicine.  He also is an angel investor and sits on the Board of two digital health startups and the Web3D Consortium, a nonprofit trade organization that maintains an open, royalty free, ISO ratified 3D standard for the web. 

To get updates on Future of Virtual Reality posts, sign up here.

 Link: http://singularityhub.com

Imagen de System Administrator

Big Data in Healthcare: The Five Most Enticing Insights

de System Administrator - lunes, 31 de agosto de 2015, 13:18
 

Big Data in Healthcare: The Five Most Enticing Insights

With a tangled web of disparate legacy systems, significant site-by-site customization, and growing regulatory scrutiny, healthcare organizations face unenviable data challenges. However, along with challenge comes opportunity. A recent study focused on analytics in the healthcare space highlighted some of the performance implications of delivering timely insights to key decision makers.

Please read the attached PDF.

Imagen de System Administrator

Big Data: The Godzilla of Healthcare

de System Administrator - jueves, 7 de agosto de 2014, 16:13
 

Big Data: The Godzilla of Healthcare

 

by Jenn Riggle

If you grew up watching Creature Double Feature movies, you know that Godzilla is a giant dinosaur-like monster that destroys Japan (and most recently San Francisco), and battles other monstrous creatures like Mothra and Destoroyah. In the early movies, Godzilla was the villain, but in the later movies he became a giant, albeit destructive, anti-hero. By the same token, big data can be a hero and save the day, or it can be a big, scary monster.

In its most basic form, big data is digital health information that comes from a variety of sources, including electronic health records, clinical trials, insurance claims, mobile apps like Fitbit and social media, where people post information about their health issues.

The power of big data is indisputable, but is it a force for good or evil?

Healthcare Hero?

A recent PwC study reported that 95 percent of healthcare CEOs said they were exploring better ways to harness and manage big data. Why are they so committed to exploring new ways to do this?

Experts predict that big data could improve everything from the drug-discovery process to predictions about patients' disease risks. In fact, a McKinsey and Co. report estimated that big data could help reduce U.S. healthcare expenses by as much as $450 billion.

Here are some ways big data can transform healthcare:

  • Population health: Big data could allow physicians to study larger populations and analyze the data to cost-effectively implement treatment changes quickly to improve people's lives.
  • Preventive care: Carolinas HealthCare System, an integrated delivery network with 900 service locations in North Carolina and South Carolina, purchased consumer spending data to analyze purchases and anticipate patients' future healthcare needs. For example, if a patient buys a lot of alcohol or eats a lot of fast food, he or she could be at a risk for depression or diabetes.
  • Reduce healthcare costs: The July issue of Health Affairsidentified six ways that big data can help reduce healthcare costs, including improving treatment for high-cost patients; reducing readmissions; improving patient triage; treating patients with deteriorating health conditions; decreasing adverse events; and treating people with diseases that affect multiple systems.
  • Organ transplant matching: Hospitals can also use big data to find matching organ donors. Economic professors developed an algorithm to find organs for previously incompatible pairs that takes into account blood type, antibody information of the candidate and the antigen information of the donor. A Carnegie Mellon professor created an advanced algorithm to create a kidney exchange network featuring donor chains. The result: people can get the organs they need to lead healthy lives.

Scary Monster?

However, even with these promising outcomes, big data is still a giant, destructive monster. The problem facing big data is that no one has answered two very important questions:

  • What is the right way to collect this information?
  • Who should be allowed access to this data?

 

Federal Trade Commissioner Julie Brill expressed concernsabout the way smartphone apps and mobile devices are collecting health information and sharing it with third parties. In addition, a recent FTC study reported that health app developers have collected consumer health data and shared it with third-parties, including marketers.

The fact that mobile companies share people's health data with third-parties, without notifying people, raises some major legal and ethical concerns. There aren't any accepted standards for how patients agree to have their information used and shared.

One terrifying scenario would be if this data is collected and shared with the wrong people. Imagine if the number of steps people walk a day, the number of hours they sleep per night, their blood pressure scores and whether they buy alcohol on a regular basis is shared with insurance companies. Independently, these facts might not mean anything, but together, they might indicate that people are at higher risk for diabetes or heart disease and insurance companies could raise their insurance rates.

There are also concerns about whether the data used in predictive analysis is clean. While the data from the patient’s medical record may be accurate, the data from external sources may not be. Combining data from different sources could impact the accuracy of the conclusions and ultimately, lead to prescribing the wrong treatment.

Time will tell whether big data will save the day or destroy the world. But either way, the healthcare landscape will change dramatically. Let's just hope we won't have giant monsters battling in U.S. cities, smashing buildings, squashing cars and making a giant mess of things. Healthcare reform is one thing, but giant monsters that breathe radioactive steam is something completely different.

Jenn Riggle is a vice president at Weber Shandwick Worldwide based in Washington, District of Columbia and member of its healthcare practice.

Link: http://www.hospitalimpact.org/index.php/2014/08/07/big_data_the_godzilla_of_healthcare

Imagen de System Administrator

Bill Gates: The next outbreak? We’re not ready

de System Administrator - viernes, 3 de abril de 2015, 17:51
 

Bill Gates: The next outbreak? We’re not ready

In 2014, the world avoided a horrific global outbreak of Ebola, thanks to thousands of selfless health workers -- plus, frankly, thanks to some very good luck. In hindsight, we know what we should have done better. So, now's the time, Bill Gates suggests, to put all our good ideas into practice, from scenario planning to vaccine research to health worker training. As he says, "There's no need to panic ... but we need to get going."

Video: http://www.ted.com

 


Página: (Anterior)   1  2  3  4  5  6  7  8  9  10  ...  38  (Siguiente)
  TODAS