Pediatric quality measures: The leap from process to outcomes.

Value-based reimbursement arrangements tie financial incentives to achieving quality measures to ensure savings are not from withholding care. For patients and their families, the delivery of high-quality care is simply the expectation. Defining and measuring pediatric quality, however, is not standardized which has led to a large proliferation of metrics across multiple stakeholders. The majority of these measures are process rather than outcomes metrics often chosen for the ease at which the data can be obtained. In order to drive greater value, outcomes measures should be preferentially selected. However, measuring outcomes in children presents multiple unique challenges. Compared to adults, children are generally healthier, their outcomes may take more time to manifest, and their clinical variability is greater. Another challenge is the amount of healthcare data being generated by providers, provider networks, payors, government agencies, and many others. This should help in understanding pediatric quality outcomes, but the massive volume of data requires new analytic tools. Artificial intelligence techniques such as machine learning offer faster, more precise, and larger scale evaluation of quality outcomes. Its implementation necessitates identifying expertise in the way of data scientists as well as additional infrastructure components to evaluate data governance, security, regulatory compliance, and ethics. Despite these prerequisites, much progress is being made in outcome insights that drive value benefiting children and families.

Experiments towards the synthesis of the ergot alkaloids and related structures. Part 8. The total synthesis of 4-methyl-2,3,4,4a,5,6-hexahydrobenzo[f]quinoline-2-carbonitrile hydrochloride hemihydrate, an immediate precursor of the despyrrole analogues of lysergic acid and its amides.

Exposure of the N-methoxycarbonyl-bicyclic-keto-acid 5 (improved preparation) to the Barnick beta-keto-acid synthesis yielded an aqueous solution of the sodium salts of the beta-keto-acids 26 and 27 which on heating at 60-65 degrees C furnished the N-methoxycarbonyl-tricyclic-ketone 9 (55%) plus the hydroxy-ketone 28 which on acid treatment raised the yield of 9 to 68%. Reduction (NaBH4) of 9 yielded the alcohol 32 (94%) which was treated with thionyl chloride followed by copper (I) cyanide and sodium iodide in acetonitrile to give the tricyclic-N-methoxycarbonyl nitrile 35 whose relative configuration was obtained by X-ray analysis. Attempts to remove the N-methoxycarbonyl group from 35 were unsuccessful. Conversion of the alcohol 32 to its methoxypropyl ether 41 followed by reaction with ethereal MeLi-LiBr yielded the amino-alcohol 39 (75%) converted to the N-formyl-tricyclic alcohol 42 with formic-acetic anhydride (70%). The alcohol 42 was then converted into the N-formyl nitrile 44 via the chloride 43 as employed in the earlier synthesis of the nitrile 35. Removal of the N-formyl group from the nitrile 44 was achieved by refluxing methanolic hydrochloric acid to give the required amino-nitrile hydrochloride 46 (91%) whose structure was confirmed by X-ray analysis. Reaction of the free base with methyl iodide in ethyl acetate in the presence of calcium carbonate furnished the N-methyl base 48 isolated as its hydrochloride, hemihydrate 49 (59%). The overall yield of 49 via this eleven-step synthesis was 3.4%.