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1.
Kidney Med ; 3(4): 565-575.e1, 2021.
Article in English | MEDLINE | ID: mdl-34401724

ABSTRACT

RATIONALE & OBJECTIVE: Digital health system tools to support shared decision making and preparation for kidney replacement treatments for patients with chronic kidney disease (CKD) are needed. STUDY DESIGN: Descriptive study of the implementation of digital infrastructure to support a patient-centered health system intervention. SETTING & PARTICIPANTS: 4 CKD clinics within a large integrated health system. EXPOSURE: We developed an integrated suite of digital engagement tools to support patients' shared decision making and preparation for kidney failure treatments. Tools included an automated CKD patient registry and risk prediction algorithm within the electronic health record (EHR) to identify and prioritize patients in need of nurse case management to facilitate shared decision making and preparation for kidney replacement treatments, an electronic patient-facing values clarification tool, a tracking application to document patients' preparation for treatments, and an EHR work flow to broadcast patients' treatment preferences to all health care providers. OUTCOMES: Uptake and acceptability. ANALYTIC APPROACH: Mixed methods. RESULTS: From July 1, 2017, through June 30, 2018, the CKD registry identified 1,032 patients in 4 nephrology clinics, of whom 243 (24%) were identified as high risk for progressing to kidney failure within 2 years. Kidney Transitions Specialists enrolled 117 (48%) high-risk patients by the end of year 1. The values tool was completed by 30/33 (91%) patients who attended kidney modality education. Nurse case managers used the tracking application for 100% of patients to document 287 planning steps for kidney replacement therapy. Most (87%) high-risk patients had their preferred kidney replacement modality documented and displayed in the EHR. Nurse case managers reported that the tools facilitated their identification of patients needing support and their navigation activities. LIMITATIONS: Single institution, short duration. CONCLUSIONS: Digital health system tools facilitated rapid identification of patients needing shared and informed decision making and their preparation for kidney replacement treatments. FUNDING: This work was supported through a Patient-Centered Outcomes Research Institute (PCORI) Project Program Award (IHS-1409-20967). TRIAL REGISTRATION: ClinicalTrials.gov NCT02722382.

2.
Crit Care Med ; 46(4): 506-512, 2018 04.
Article in English | MEDLINE | ID: mdl-29293143

ABSTRACT

OBJECTIVES: To determine the clinical characteristics and outcomes of culture-negative septic shock in comparison with culture-positive septic shock. DESIGN: Retrospective nested cohort study. SETTING: ICUs of 28 academic and community hospitals in three countries between 1997 and 2010. SUBJECTS: Patients with culture-negative septic shock and culture-positive septic shock derived from a trinational (n = 8,670) database of patients with septic shock. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Patients with culture-negative septic shock (n = 2,651; 30.6%) and culture-positive septic shock (n = 6,019; 69.4%) were identified. Culture-negative septic shock compared with culture-positive septic shock patients experienced similar ICU survival (58.3% vs 59.5%; p = 0.276) and overall hospital survival (47.3% vs 47.1%; p = 0.976). Severity of illness was similar between culture-negative septic shock and culture-positive septic shock groups ([mean and SD Acute Physiology and Chronic Health Evaluation II, 25.7 ± 8.3 vs 25.7 ± 8.1]; p = 0.723) as were serum lactate levels (3.0 [interquartile range, 1.7-6.1] vs 3.2 mmol/L [interquartile range, 1.8-5.9 mmol/L]; p = 0.366). As delays in the administration of appropriate antimicrobial therapy after the onset of hypotension increased, patients in both groups experienced congruent increases in overall hospital mortality: culture-negative septic shock (odds ratio, 1.56; 95% CI [1.47-1.66]; p < 0.0001) and culture-positive septic shock (odds ratio, 1.65; 95% CI [1.59-1.71]; p < 0.0001). CONCLUSIONS: Patients with culture-negative septic shock behave similarly to those with culture-positive septic shock in nearly all respects; early appropriate antimicrobial therapy appears to improve mortality. Early recognition and eradication of infection is the most obvious effective strategy to improve hospital survival.


Subject(s)
Hospital Mortality/trends , Intensive Care Units/statistics & numerical data , Shock, Septic/mortality , Time-to-Treatment/statistics & numerical data , APACHE , Aged , Anti-Bacterial Agents/administration & dosage , Blood Culture , Body Temperature , Comorbidity , Female , Heart Rate , Humans , Hypotension/etiology , Hypotension/therapy , Lactic Acid/blood , Male , Middle Aged , Respiration, Artificial , Retrospective Studies , Shock, Septic/complications , Time Factors
3.
J Pain Symptom Manage ; 50(3): 343-349.e6, 2015 Sep.
Article in English | MEDLINE | ID: mdl-25982156

ABSTRACT

CONTEXT: With growing emphasis on improving the value of health care, there is increased scrutiny of quality outcomes and high health expenditures during the final months of life. OBJECTIVES: The purpose of this project is to answer 1) how do next of kin (NOK) perceive the quality of their loved ones' dying and death; 2) are there patient and NOK characteristics that predict lower quality; and 3) are there structural aspects of care associated with lower quality? METHODS: A mailed survey was administered to a stratified random sample of NOK of Geisinger Health System patients who had died in the past year. The Quality of Death and Dying, the General Anxiety Disorder seven-item scale, the Patient Health Questionnaire eight-item depression scale, and selected questions from the Toolkit of Instruments to Measure End of Life Care were used. RESULTS: There were 672 respondents. Significant predictors of Quality of Death and Dying score were number of doctors involved in care (P = 0.0415), location of death (P < 0.0001), frequency of receiving confusing or contradictory information (P < 0.0001), illness progression (P = 0.0343), Patient Health Questionnaire-2 score (P = 0.0148), and General Anxiety Disorder seven-item scale score (P < 0.0070). CONCLUSION: Several findings suggest that factors such as NOK depression and anxiety, prolonged illness, dying in the hospital, receipt of conflicting information, and confusion around the doctor in charge are associated with lower quality of the dying and death experience for NOK. Further investigation is warranted to facilitate high-quality measurement and the use of measurement results to improve care.


Subject(s)
Death , Delivery of Health Care, Integrated/methods , Quality Assurance, Health Care , Terminal Care/methods , Adolescent , Adult , Aged , Aged, 80 and over , Anxiety , Communication , Depression , Family/psychology , Female , Humans , Male , Middle Aged , Pennsylvania , Physicians , Quality Assurance, Health Care/methods , Quality of Life , Rural Population , Terminal Care/psychology , Young Adult
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