“…Thus, when preparing hip fracture patients for successful community discharge following rehabilitation, PAC providers must attend to both facilitating the prevention of adverse medical events and providing patients and caregiver(s) with the skills and knowledge needed to manage new functional limitations so they may fully participate, long-term, in their home and community environments. 30–33 Due to the unique care needs of hip fracture PAC patients and the distinctive focus of rehabilitation services, an additional quality measure, complementary to the 30-day readmission rate measure, is needed to better reflect the quality of PAC.…”
Background
Post-acute care (PAC) rehabilitation aims to maximize independence and facilitate a safe community transition. Yet little is known about PAC patients’ success in staying home post-discharge or differences on this outcome across PAC providers.
Objectives
Examine the percentage of PAC patients who remain in the community at least 30 days after discharge (i.e., successful community discharge) following hip fracture rehabilitation and describe differences among PAC facilities based on this outcome.
Research Design
Retrospective observational study.
Subjects
Community-dwelling, Medicare fee-for-service beneficiaries 75 years of age and older who experienced their first hip fracture between 1999–2007 (n=880,779). PAC facilities admitting hip fracture patients in 2006.
Measures
Successful community discharge, sites of readmission after PAC discharge.
Results
Between 1999 and 2007, 57% of patients achieved successful community discharge. Black were less likely (adjusted odds ratios=0.84, 95% confidence interval 0.82–0.86) than similar whites to achieve successful community discharge. Among all who re-entered the community (n=581,095), 14% remained in the community fewer than 30 days. Acute hospitals (67.5%) and institutional PAC (16.8%) were the most common sites of re-entry. The median proportion of successful community discharge among facilities was 49% (IQR: 33%–66%). Lowest-quartile facilities admitted older (85.9 vs. 84.1 years of age), sicker patients (e.g., higher rates of hospital complications 6.0% vs. 4.6%), but admitted fewer annually (7.1 vs. 19.3), compared to the highest quartile.
Conclusions
Re-entry into the healthcare system after PAC community discharge is common. Due to the distinct care needs of the PAC population there is a need for a quality measure that complements the current 30-day hospital readmission outcome and captures the objectives of PAC rehabilitation.
“…Thus, when preparing hip fracture patients for successful community discharge following rehabilitation, PAC providers must attend to both facilitating the prevention of adverse medical events and providing patients and caregiver(s) with the skills and knowledge needed to manage new functional limitations so they may fully participate, long-term, in their home and community environments. 30–33 Due to the unique care needs of hip fracture PAC patients and the distinctive focus of rehabilitation services, an additional quality measure, complementary to the 30-day readmission rate measure, is needed to better reflect the quality of PAC.…”
Background
Post-acute care (PAC) rehabilitation aims to maximize independence and facilitate a safe community transition. Yet little is known about PAC patients’ success in staying home post-discharge or differences on this outcome across PAC providers.
Objectives
Examine the percentage of PAC patients who remain in the community at least 30 days after discharge (i.e., successful community discharge) following hip fracture rehabilitation and describe differences among PAC facilities based on this outcome.
Research Design
Retrospective observational study.
Subjects
Community-dwelling, Medicare fee-for-service beneficiaries 75 years of age and older who experienced their first hip fracture between 1999–2007 (n=880,779). PAC facilities admitting hip fracture patients in 2006.
Measures
Successful community discharge, sites of readmission after PAC discharge.
Results
Between 1999 and 2007, 57% of patients achieved successful community discharge. Black were less likely (adjusted odds ratios=0.84, 95% confidence interval 0.82–0.86) than similar whites to achieve successful community discharge. Among all who re-entered the community (n=581,095), 14% remained in the community fewer than 30 days. Acute hospitals (67.5%) and institutional PAC (16.8%) were the most common sites of re-entry. The median proportion of successful community discharge among facilities was 49% (IQR: 33%–66%). Lowest-quartile facilities admitted older (85.9 vs. 84.1 years of age), sicker patients (e.g., higher rates of hospital complications 6.0% vs. 4.6%), but admitted fewer annually (7.1 vs. 19.3), compared to the highest quartile.
Conclusions
Re-entry into the healthcare system after PAC community discharge is common. Due to the distinct care needs of the PAC population there is a need for a quality measure that complements the current 30-day hospital readmission outcome and captures the objectives of PAC rehabilitation.
“…However, we recommend creating one single document before the scheduled discharge and labeling it 'Preliminary DS' before handing it to the patient. This process is less labor-intensive because the writing physician may recall more details of the case [47]. Pending results can be added later in the same document before the complete DS is transmitted to the GP after being approved by senior doctors [6].…”
Section: Discussionmentioning
confidence: 99%
“…Especially for doctors in training, the intellectually most challenging section of the DS is the clinical summary or narrative or synopsis considering the limited clinical experience and presentation skills of younger doctors, as a study by Kind et al has shown [47]. Unfortunately, there are limited recommendations in the literature regarding how to write this portion of the DS [44,65].…”
Section: Discussionmentioning
confidence: 99%
“…According to recent research, a timely DS can reduce hospital readmission, among other factors [64]. The delayed creation of DS is associated with a higher error rate [47]. Since 2010, for UK National Health Service healthcare trusts, it is mandatory to send a standardized DS within 24 h after discharge from the hospital to the GP ('Clinical Data Standards Assurance Programme') [43].…”
“…Although this does not yield the same amount of information as a patient's entire medical record, it contains information that is succinct and is a synopsis of the patient's hospitalization history. Analysis of the information in these summaries can provide insight to important metrics related to case mix, epidemiology, adverse events, outcomes and so forth which were either previously unknown or difficult to assimilate given the resource constraints in the healthcare setting [4][5][6][7].…”
Section: This Article Is Part Of the Topical Collection On Patient Famentioning
Electronic Health Record (EHR) use in India is generally poor, and structured clinical information is mostly lacking. This work is the first attempt aimed at evaluating unstructured text mining for extracting relevant clinical information from Indian clinical records. We annotated a corpus of 250 discharge summaries from an Intensive Care Unit (ICU) in India, with markups for diseases, procedures, and lab parameters, their attributes, as well as key demographic information and administrative variables such as patient outcomes. In this process, we have constructed guidelines for an annotation scheme useful to clinicians in the Indian context. We evaluated the performance of an NLP engine, Cocoa, on a cohort of these Indian clinical records. We have produced an annotated corpus of roughly 90 thousand words, which to our knowledge is the first tagged clinical corpus from India. Cocoa was evaluated on a test corpus of 50 documents. The overlap F-scores across the major categories, namely disease/symptoms, procedures, laboratory parameters and outcomes, are 0.856, 0.834, 0.961 and 0.872 respectively. These results are competitive with results from recent shared tasks based on US records. The annotated corpus and associated results from the Cocoa engine indicate that unstructured text mining is a viable method for cohort analysis in the Indian clinical context, where structured EHR records are largely absent.
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